Data Scientist (LLM)

🏢 Summary: The role focuses on designing, building, and optimizing AI-driven backend systems that power a large-scale conversational assistant with low-latency, high-availability requirements. You will work across Java/Kotlin and Python ecosystems to implement LLM orchestration, RAG pipelines, and semantic search solutions within a cloud-native microservices architecture. The position involves full ownership of AI microservices and data pipelines from design to deployment in a production-scale environment. 🗂️ Requirements: Proficiency in Python, Proficiency in Java, Proficiency in Kotlin, Experience with LLM orchestration and RAG, Experience with microservices architecture, Experience with vector search and semantic search, Experience with cloud-native environments, Ability to design and optimize high-availability, low-latency systems, English level B2 or higher 📃 Skills: Python, Java, Kotlin, Spring, ADK, LangChain, Langfuse, LLM, RAG, Kubernetes, Docker, Consul, GitHub, GitHubActions, VectorSearch, Microservices 🏢 Description: About the job: Performance & Scale: Design, build, and optimize AI-driven systems that process complex natural language interactions. Delivering low-latency, high-quality responses from our AI Assistant requires high-availability and smart optimization of LLM and retrieval workloads in practice. Modern Tech Stack: Work with a world-class, cloud-native polyglot environment. Our core backend technologies include Java , Kotlin , Spring, and ADK . At the same time, our AI and orchestration layer heavily relies on Python . You will utilize Python and LangChain for complex LLM orchestration, alongside Langfuse for observability, prompt tracking, and evaluation. We leverage advanced vector search and modern ML solutions to make our assistant truly smart. True Ownership & Autonomy: We live by a "you build it, you run it" philosophy. You'll join an agile, autonomous team with full ownership of your AI microservices and data pipelines, from design to deployment; and improvements are dictated by results of our own experiments and AI evaluation metrics. Complex Challenges: From LLM orchestration and Retrieval-Augmented Generation (RAG) to semantic search optimization, you'll tackle the complex backend problems that power a conversational marketplace assistant. You will work across the Java/Kotlin and Python ecosystems, integrating advanced embedding models, prompt pipelines, and vector databases to ensure our AI deeply understands and accurately retrieves information. In our domain, we focus on delivering the core search and retrieval capabilities for the Allegro AI Assistant. We maintain a critical entry point for users looking to discover products, compare offers, and get personalized recommendations through natural conversations. Striving for relevancy and accuracy first, we are designing, implementing, and operating an extensive system combining modern microservice architecture with Large Language Models, high-performance retrievers, and vast data sources. We care about data quality, robust context building, and near real-time accuracy to best guide users through a highly dynamic marketplace via an intelligent, conversational interface. Important things for you: Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. The salary range for this position depending on the skill set is as follows (contract of employment, tax-deductible cost): PLN 14 600 - 20 825 Annual bonus based on your annual performance and company results. Our team is based in Poznań. We are looking for people who: Code in Python, Java and Kotlin ; Expect work that requires creative approach to search experience challenges, to be proud of enjoying its results together with all Allegro users; Want to create solid code, eagerly accept comments and share knowledge during code reviews; Can look for effective solutions to the requirements set by users; Want to constantly develop and update their knowledge; Know English at at least B2 level. Nice to have: You are open to diverse technologies and workflows, including dev-operational tools on one hand, and working with data on the other. Basic experience with LLM tuning (LoRA, PEFT), training and evaluation pipelines for models and/or basic frameworks for building AI Agents (Agent Development Kit, LangChain, AutoGen, CrewAI) would be great! What's in it for you: Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. And that's just the beginning! You can read more about the benefits here . #goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale , which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about! Send us your CV and… see you at Allegro!

🏢 Summary: Engineering role focused on designing, building, and optimizing AI-driven microservices that power a conversational marketplace assistant. The position involves LLM orchestration, Retrieval-Augmented Generation, semantic search, and high-performance retrieval in a cloud-native environment. You will own end-to-end development of AI services across Java/Kotlin and Python ecosystems, ensuring scalability, low latency, and high availability. 🗂️ Requirements: Proficiency in Python, Proficiency in Java, Proficiency in Kotlin, Experience with LLM orchestration, Experience with Retrieval-Augmented Generation (RAG), Experience with semantic search and vector search, Experience building microservices, Experience with cloud-native architectures, Ability to design and optimize high-availability systems, English level B2 or higher 📃 Skills: Python, Java, Kotlin, Spring, ADK, LangChain, Langfuse, LLM, RAG, LoRA, PEFT, AutoGen, CrewAI, Kubernetes, Docker, Consul, GitHub, GitHubActions, VectorSearch, Embeddings 🏢 Description: About the job: Performance & Scale: Design, build, and optimize AI-driven systems that process complex natural language interactions. Delivering low-latency, high-quality responses from our AI Assistant requires high-availability and smart optimization of LLM and retrieval workloads in practice. Modern Tech Stack: Work with a world-class, cloud-native polyglot environment. Our core backend technologies include Java , Kotlin , Spring, and ADK . At the same time, our AI and orchestration layer heavily relies on Python . You will utilize Python and LangChain for complex LLM orchestration, alongside Langfuse for observability, prompt tracking, and evaluation. We leverage advanced vector search and modern ML solutions to make our assistant truly smart. True Ownership & Autonomy: We live by a "you build it, you run it" philosophy. You'll join an agile, autonomous team with full ownership of your AI microservices and data pipelines, from design to deployment; and improvements are dictated by results of our own experiments and AI evaluation metrics. Complex Challenges: From LLM orchestration and Retrieval-Augmented Generation (RAG) to semantic search optimization, you'll tackle the complex backend problems that power a conversational marketplace assistant. You will work across the Java/Kotlin and Python ecosystems, integrating advanced embedding models, prompt pipelines, and vector databases to ensure our AI deeply understands and accurately retrieves information. In our domain, we focus on delivering the core search and retrieval capabilities for the Allegro AI Assistant. We maintain a critical entry point for users looking to discover products, compare offers, and get personalized recommendations through natural conversations. Striving for relevancy and accuracy first, we are designing, implementing, and operating an extensive system combining modern microservice architecture with Large Language Models, high-performance retrievers, and vast data sources. We care about data quality, robust context building, and near real-time accuracy to best guide users through a highly dynamic marketplace via an intelligent, conversational interface. Important things for you: Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. The salary range for this position depending on the skill set is as follows (contract of employment, tax-deductible cost): PLN 14 200 - 20 200 Annual bonus based on your annual performance and company results. Our team is based in Poznań. We are looking for people who: Code in Python, Java and Kotlin ; Expect work that requires creative approach to search experience challenges, to be proud of enjoying its results together with all Allegro users; Want to create solid code, eagerly accept comments and share knowledge during code reviews; Can look for effective solutions to the requirements set by users; Want to constantly develop and update their knowledge; Know English at at least B2 level. Nice to have: You are open to diverse technologies and workflows, including dev-operational tools on one hand, and working with data on the other. Basic experience with LLM tuning (LoRA, PEFT), training and evaluation pipelines for models and/or basic frameworks for building AI Agents (Agent Development Kit, LangChain, AutoGen, CrewAI) would be great! What's in it for you: Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. And that's just the beginning! You can read more about the benefits here . #goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale , which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about! Send us your CV and… see you at Allegro!

🏢 Summary: The offer is for a Software Engineer (Agent Development) role focused on building and scaling production-ready AI agents and autonomous marketing workflows. The position combines strong backend engineering with applied GenAI, emphasizing reliable, scalable systems integrated into a live marketing automation platform. The role involves working with LLM orchestration, backend services, and AI-driven integrations in a fast-paced, collaborative environment. 🗂️ Requirements: 2–4 years of software engineering experience, Strong experience in Python and scalable backend development, Understanding of building production-ready, maintainable systems, Interest in AI, GenAI, and agentic systems, Experience with backend databases such as MySQL, Redis, or DynamoDB, Ability to work in fast-paced, iterative environments, Strong problem-solving skills, Ability to collaborate with cross-functional and distributed teams 📃 Skills: Python, GenAI, LLM, MySQL, Redis, DynamoDB, APIs, CI/CD, Cloud, AI, Agents 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Agent Development) to join our client’s growing AI team and help build the next generation of autonomous AI agents powering modern marketing workflows. In this role, you’ll work at the intersection of backend engineering and applied AI, designing and scaling production-ready agentic systems used by businesses worldwide. This is not a pure research role. The focus is on strong software engineering fundamentals and building reliable, scalable AI-powered products. You’ll work across backend systems, orchestration, integrations, and AI workflows, collaborating closely with cross-functional product and engineering teams. The environment is fast-paced and highly collaborative, with a strong emphasis on ownership, rapid iteration, and building real-world AI solutions already running in production. Key takeaways: Stack: Python, AI Agents, MySQL, GenAI Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Technical interview, live coding (1h) Cross-functional interview (1h) Interview with Hiring Manager (45 min) | Optional Responsibilities: Design and develop production-grade AI agents and autonomous marketing workflows across the platform. Build and maintain multi-step agentic systems involving LLM orchestration, tool usage, and backend integrations. Work with LLM APIs, including prompt engineering, response handling, evaluation, and optimization of AI workflows. Create and improve evaluation frameworks, quality metrics, and monitoring processes to ensure agent reliability and performance at scale. Monitor and optimize agent behavior, latency, token usage, cost efficiency, and production stability. Develop production-quality backend services and orchestration layers primarily using Python. Contribute to backend and frontend integration points where AI agents interact with the core platform. Build and maintain APIs, service interfaces, and data flows supporting AI-driven capabilities. Collaborate closely with Product, Design, and Engineering teams to define and deliver AI-powered user experiences. Ensure code quality through testing, code reviews, and adherence to engineering best practices. Participate in on-call rotations supporting AI agent services and platform reliability. Contribute to technical documentation, architectural decisions, and AI engineering best practices. Collaborate closely with globally distributed teams, including regular overlap with US-based stakeholders. Requirements: 2–4 years of experience in software engineering, with strong backend development fundamentals. Strong hands-on experience with Python and building scalable backend services. Interest in AI, GenAI, and agentic systems, with a willingness to grow in this area professionally. Exposure to AI-related projects, LLM-based solutions, ML models, or personal AI experiments is considered a strong plus. Understanding of how to build reliable, maintainable, and production-ready systems. Ability to work in fast-paced, iterative environments and ship code quickly while maintaining engineering quality. Familiarity with modern backend and database technologies such as MySQL, Redis, or DynamoDB. Strong problem-solving skills and the ability to work across different systems and technologies. Experience with cloud environments, APIs, CI/CD practices, or observability tooling is a plus. Familiarity with AI agent frameworks, prompt engineering, or LLM workflows is nice to have, but not required. Strong communication skills and a collaborative mindset within cross-functional engineering teams. Willingness to collaborate with globally distributed teams, including regular overlap with US-based stakeholders. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.

🏢 Summary: Senior Data Scientist role focused on leading the design and delivery of production-grade Generative AI solutions using LLMs, including RAG pipelines, chatbots, and AI agents. The position combines hands-on development with architectural decision-making and technical mentorship, delivering scalable GenAI systems for large enterprise clients. You will own the full lifecycle from solution discovery through deployment, safety, and optimization. 🗂️ Requirements: 6+ years experience in Data Science or AI engineering, 4+ years production experience with Python for AI/ML, 2+ years building and deploying LLM-based systems in production, Experience designing and implementing RAG pipelines, Experience with model fine-tuning techniques (LoRA, QLoRA, SFT), Experience building end-to-end GenAI applications including orchestration and APIs, Ability to design system architectures for LLM-based solutions, Experience implementing AI safety and governance controls, Strong analytical and problem-solving skills, Professional English communication skills 📃 Skills: Python, LLMs, LangChain, LlamaIndex, LangGraph, RAG, LoRA, QLoRA, SFT, APIs, VectorDB, AI, MachineLearning 🏢 Description: ABOUT THE COMPANY Our client is an end-to-end data services partner to global enterprises, founded in 2008 and headquartered in Warsaw. Our teams work with over 75 leading consumer packaged goods brands across more than 30 countries, helping them unlock the full value of their data — from strategy and development through to operations and adoption. Our work spans supply chain analytics, customer analytics, AI and machine learning, data platforms, and digital commerce. We are recognised as a Strong Performer in the Gartner Peer Insights Voice of the Customer report for data and analytics, and hold Great Place to Work certification in multiple countries. ABOUT THE ROLE We're looking for an experienced Senior Data Scientist with deep expertise in Generative AI to lead projects building and implementing advanced LLM-based systems — including chatbots, AI agents, and RAG pipelines. This is a technical leadership role: you'll make architectural decisions, select technologies, set best practices, and mentor other engineers, while remaining hands-on across the full solution lifecycle. You'll work closely with data engineers, product owners, and full-stack developers to deliver scalable GenAI applications for large enterprise clients, primarily in CPG, retail, and manufacturing. WHAT YOU'LL WORK ON Solution design and discovery Lead discovery and solution design for GenAI use cases — translating business problems into concrete architectures covering LLM selection, RAG, fine-tuning, agents, and guardrails. End-to-end GenAI applications Build complete GenAI solutions covering data ingestion, retrieval layers, orchestration (LangChain, LlamaIndex, LangGraph), API and backend, and lightweight UI where needed. RAG pipeline design Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness. Model selection, prompting, and fine-tuning Own prompting strategies, model selection, and fine-tuning (LoRA, QLoRA, SFT) for text, code, and multimodal models, including evaluation and A/B testing. Safety and governance Implement safety, compliance, and governance controls including input/output filters, PII handling, audit logs, and human-in-the-loop review where required. Requirements and estimation Gather technical requirements from stakeholders and produce reliable estimates for planned work. Mentorship and knowledge sharing Mentor other data scientists and engineers in GenAI patterns, code quality, and best practices. Contribute to internal libraries, templates, and reusable components. Staying current Track the GenAI landscape — new open and hosted models, agentic frameworks, evaluation techniques — and run targeted PoCs to validate emerging approaches. WHAT WE LOOK FOR 6+ years in Data Science or AI engineering Broad experience across the data science and AI stack, with a track record of delivering production systems. 4+ years of production Python for AI Fluent in writing production-ready Python for AI and ML workloads — clean, maintainable, and deployable. 2+ years of production LLM development Hands-on experience building and shipping LLM-based systems in production environments, not just research or prototypes. Strong analytical and problem-solving skills Able to break down ambiguous problems, make sound architectural decisions under uncertainty, and defend those decisions clearly. Excellent English communication Comfortable working directly with international clients and cross-functional teams. Able to translate technical complexity for non-technical stakeholders. THE TEAM You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates. COMPENSATION & BENEFITS Rate 105 – 170 PLN per hour on a B2B contract, depending on experience. Work model Fully remote or office-based — your choice. Flexibility on working hours and contract form. Workation policy Option to work remotely from other locations for defined periods. Onboarding Comprehensive online onboarding programme with a dedicated buddy from day one. Learning and development Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year. Career growth Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation. Referral bonuses Financial rewards for successful employee referrals. Wellbeing Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives. Equipment Modern office equipment provided. Employer recognition Great Place to Work certified employer.

🏢 Summary: Hands-On Engineering Manager role focused on building and shipping AI-native, agentic banking products that operate across voice, chat, and digital channels. The position involves architecting low-latency distributed backend systems, orchestrating multi-agent LLM workflows, and leading a high-performance engineering team while remaining deeply hands-on. The goal is to deliver production-grade AI systems that autonomously power real-time financial customer experiences. 🗂️ Requirements: 8+ years backend engineering experience, Experience building distributed systems, Experience with low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating systems with LLMs, 2+ years engineering management or technical leadership experience, Experience designing and orchestrating agentic workflows, Proficiency in Typescript and/or at least two backend languages, Strong understanding of distributed systems, concurrency, reliability, Experience deploying AI systems in cloud environments, Experience building high-concurrency, fault-tolerant systems, Experience implementing observability, monitoring, and testing for production systems, Experience ensuring security and safe handling of financial data 📃 Skills: Typescript, Node.js, Go, Java, Rust, LLM, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, Chat, APIs, Cloud, Observability, Monitoring, Testing, Security, ReinforcementLearning, MultiAgentSystems 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Hands-On Engineering Manager role focused on building and orchestrating AI-native, agentic systems for real-time voice and chat in banking. The position combines deep backend distributed systems expertise with LLM-driven multi-agent architectures to deliver low-latency, production-grade AI products. You will lead a high-performance team while remaining hands-on in architecting and shipping scalable, reliable AI systems. 🗂️ Requirements: 8+ years backend engineering experience in distributed systems, Experience building low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating and orchestrating LLMs, 2+ years engineering management or technical leadership experience, Strong proficiency in TypeScript and/or at least two backend languages (Node.js, Go, Java, Rust), Deep understanding of distributed systems, concurrency, and reliability, Experience deploying AI systems in cloud environments, Experience designing agentic workflows and multi-agent systems 📃 Skills: TypeScript, Node.js, Go, Java, Rust, LLMs, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, APIs, Cloud, ReinforcementLearning, Monitoring, Observability 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Hybrid Python AI Developer role focused on building AI-powered services and automation solutions using Large Language Models and agent-based workflows. The position involves developing RAG-based bots and assistants, implementing agentic workflows, and collaborating on high-quality AI frameworks. It offers the opportunity to work on advanced LLM solutions in a dynamic, innovation-driven environment. 🗂️ Requirements: Minimum 3 years of experience in software development with Python, Practical knowledge of LangChain and LangGraph, Experience with RAG, embeddings, vector search, LLM agents, agentic workflows, tool calling, At least 1 year of hands-on experience with LLM models, RAG, and AI agents in real projects, Proficiency with Git (branch management, rebase, cherry-pick, revert, squash), Familiarity with Jira, Confluence, Bitbucket, Competent command of Polish, Communicative level of English, Legal right to work in the European Union 📃 Skills: Python, LangChain, LangGraph, RAG, LLM, Embeddings, VectorSearch, Git, Jira, Confluence, Bitbucket, Azure, React, Streamlit, Databricks, CosmosDB, Redis, Grafana 🏢 Description: Unleash the future of AI by building innovative Large Language Model solutions that redefine automation and intelligence. Warszawa-based opportunity with hybrid work model (4 days remote, 1 day in the office). As a Python AI Developer , you will be working for our client, a leading innovator in AI technology. You will contribute to developing cutting-edge services and applications supporting automation processes, leveraging advanced LLM solutions and agent-based workflows. This role offers a chance to be at the forefront of AI innovation and accelerate your career growth in a dynamic environment. Your main responsibilities: Build AI-powered services and applications in Python to support automation initiatives. Develop bots and assistants based on Large Language Models, including RAG solutions and multi-step task agents. Implement agentic workflows: define roles, manage tools, and oversee execution processes. Work with internal and new AI frameworks, ensuring high quality and alignment with best practices. Collaborate with cross-functional teams to troubleshoot, analyze issues, and optimize solutions. Maintain adherence to development standards and contribute to continuous improvement initiatives. Document system designs and participate in architectural discussions. You're ideal for this role if you have: Minimum 3 years of experience in software development, particularly with Python. Practical knowledge of LangChain and LangGraph. Experience with RAG, embeddings, vector search, LLM agents, agentic workflows, and tool calling. At least 1 year of hands-on experience with LLM models, RAG, and AI agents in real projects. Proficiency with Git, including branch management and commit operations (rebase, cherry-pick, revert, squash). Familiarity with Jira, Confluence, Bitbucket. Strong problem-solving skills and ability to work independently in a collaborative environment. It is a strong plus if you have: Knowledge of Azure AI Stack (AI Foundry, Azure OpenAI, Azure AI Search). Experience with React, Streamlit, Databricks, Cosmos DB, Redis, or Grafana. Understanding of ML fundamentals and fine-tuning LLMs. Skills in high-level system architecture design and documentation. Language Required for the role: Polish – competent command. English – communicative level. Eligibility for the role: Only candidates with an existing legal right to work in the European Union will be considered. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data. Please be prepared for a live coding session during the interview process, where your technical skills will be thoroughly evaluated.

🏢 Summary: Senior AI Engineer role focused on building agentic conversational systems for recruiting, leveraging large language models and advanced NLP to create intelligent, goal-driven AI assistants. The position involves designing, developing, and deploying scalable ML pipelines and autonomous AI workflows in production. The role combines hands-on ML engineering with technical leadership in a global, cross-functional environment. 🗂️ Requirements: BSc or MSc in Computer Science, Machine Learning, AI, NLP or related field or equivalent experience, 5+ years of experience developing and deploying machine learning systems in production, Proven expertise in NLP techniques, LLM fine-tuning and model evaluation, Strong proficiency with deep learning frameworks, Advanced Python programming skills, Experience designing and maintaining end-to-end ML pipelines from data ingestion to deployment, Fluency in English, written and spoken 📃 Skills: Python, PyTorch, TensorFlow, scikit-learn, HuggingFace, NLP, LLM, MachineLearning, DeepLearning, MLOps, DataPipelines 🏢 Description: Company Description 🚀 SmartRecruiters transforms hiring for the world’s leading enterprises. We deliver an AI-powered hiring platform built for global scale, automating and optimizing the entire talent acquisition process. More than 4,000 companies, including LinkedIn, McDonald's, VISA, CD Projekt Red, Allegro rely on SmartRecruiters to build winning teams. 🚀 In 2025, SmartRecruiters joined SAP, the global leader in enterprise applications. Together, we are accelerating the reinvention of hiring by combining AI innovation with the scale and resources of SAP’s ecosystem. We designed our R&D structure based on the empowered product teams model. It means our teams are responsible for business outcomes and have autonomy in solving problems in the way that “customers love yet work for the business” (yes, we are heavily influenced by this and that ). Job Description We are looking for a Senior AI Engineer to join our Chat Group, where we’re building the next generation of intelligent conversational systems for the recruiting industry. Our mission is bold yet simple: boost the efficiency of recruiting and hiring teams and deliver the most personalized experience ever - powered by cutting-edge ML, NLP, and agentic AI You’ll play a central role in designing and developing agentic workflows, where autonomous AI agents collaborate, reason, and act to deliver intelligent and context-aware recruiting experiences at scale . At SmartRecruiters, you’ll be part of a global, high-impact team shaping how people connect with jobs.You’ll work with passionate peers across Germany, Poland, the UK, and the US - in a culture that values autonomy, innovation, and measurable outcomes. We’re not just building chat systems - we’re building the AI recruiting assistants of the future. What You’ll Do: Architect and build agentic workflows that combine large language models, reasoning components, and data pipelines to create adaptive, goal-driven conversational systems Lead the design and development of advanced ML/NLP products, from ideation to production - including model training, evaluation, optimization, and deployment Drive experimentation with new approaches for agentic reasoning, coordination, and autonomous system design Collaborate closely with product and engineering teams to integrate intelligent agents into real-world recruiting workflows Guide technical decisions, mentor other engineers, and help define best practices for scalable, maintainable ML systems Contribute to the evolution of our NLP and conversational intelligence stack, focusing on reliability, personalization, and user impact Proactively identify opportunities to automate, improve, and innovate within our chat-based ecosystem Qualifications: BSc or MSc in Computer Science, Machine Learning, AI, NLP, or a related technical field - or equivalent practical experience 5+ years of experience developing and deploying machine learning systems in production Proven expertise in NLP techniques, LLM fine-tuning, and model evaluation Strong proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow) and ML tools (e.g., scikit-learn, Hugging Face) Advanced Python programming skills and solid software engineering fundamentals Experience designing and maintaining end-to-end ML pipelines, from data ingestion to deployment Hands-on experience with agentic workflows or building autonomous AI systems is a major plus Familiarity with chatbots, conversational AI, or multi-agent systems is strongly preferred Experience with data quality management, evaluation metrics, or observability in ML systems is a plus Strong analytical thinking, creativity, and an ownership mindset Excellent communication and collaboration skills in a cross-functional, international environment Fluency in English, both written and spoken Benefits: We support 100% remote work with Wi-Fi reimbursement and an additional stipend for the equipment (the MacBook laptop is provided by us) Unlimited vacation days (yes - it's really unlimited) Private Medical Care for you and your dependents (Luxmed) Wellness Programme (Multisport Card and even more) Company wide shutdowns in August and around Christmas Additional information SmartRecruiters is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

🏢 Summary: Technical Project Manager role leading end-to-end deployment of AI Agent solutions for Tier-1 enterprise clients. Responsible for managing complex backend integrations, aligning AI engineering teams with business stakeholders, and ensuring successful delivery under high-pressure conditions. The position focuses on enterprise-scale AI implementations within banking, telco, and insurance sectors. 🗂️ Requirements: 5+ years Technical Project Management experience in B2B enterprise software, AI, or complex IT infrastructure, Proven experience delivering high-stakes enterprise projects in Banking, Telco, or Insurance, PRINCE2 certification (Foundation or Practitioner), Expert knowledge of Agile and Scrum methodologies, Ability to apply Waterfall methodology when required, Ability to read technical documentation and discuss API integrations and AI logic, Fluent Polish (C1), Fluent English (C1), Expert proficiency in Jira and Confluence 📃 Skills: Jira, Confluence, Agile, Scrum, Waterfall, PRINCE2, APIs, AI, IT, Infrastructure, Polish, English 🏢 Description: Lekta AI | Kraków / Remote Founded in 2016 in Kraków, Poland, Lekta AI is a technological company working with major European banking, insurance , and telco enterprises. The company was set up with an ambitious goal of providing the best customer service in the world. Lekta stands out from the crowd of conversational AI companies because we combine technological expertise with domain-specific knowledge of the contact center industry veterans. Through the use of our proprietary conversational neurosymbolic engine and backend integrations, our systems are intent, and context-aware, handling over 1.5 million conversations every month . We are currently in a phase of rapid international expansion and are looking for a resilient, high-stakes Technical Project Manager to lead the implementation of our Agent solutions for our most prestigious enterprise clients. The Role: As a Project Manager at Lekta AI, you aren't just moving tickets in Jira; you are the field commander for our most complex client integrations. You will be the primary bridge between our sophisticated AI engineering teams and the demanding requirements of Tier-1 enterprise stakeholders. This role requires a "steady hand at the wheel"—someone who can navigate technical bottlenecks and tight deadlines without losing focus. Key Responsibilities: ● Lead the full project lifecycle of Agent deployments, from initial technical discovery and backend integration to go-live and post-launch optimization. ● Serve as the primary point of contact for enterprise clients. Proactively identify risks, manage expectations, and maintain project momentum during complex integration phases. ● Orchestrate multidisciplinary squads (Engineers, AI Researchers, UX/UI Designers) to ensure delivery remains on track and within scope. ● Refine and scale our delivery framework. We value "repeatable excellence"—you will help build the playbooks that allow us to scale internationally. ● Use Jira, Confluence, and other PM tools to maintain meticulous documentation and resource allocation. ● Translate complex AI concepts into business value for clients, and turn client business requirements into actionable technical tasks for the dev team. Requirements: ● 5+ years in Technical Project Management, specifically within B2B enterprise software, AI, or complex IT infrastructure projects. ● A proven track record of managing high-pressure, high-stakes projects for demanding clients (Banking, Telco, or Insurance). You stay calm when the "unexpected" happens. ● Certification: PRINCE2 (Foundation or Practitioner) is highly desirable and will give you a significant advantage. ● Expert-level knowledge of Agile/Scrum, with the flexibility to apply Waterfall principles when enterprise compliance requires it. ● Technical Literacy: You must be comfortable reading technical documentation and discussing API integrations or AI logic with architects. ● Fluent Polish and English (C1) are mandatory. You must be able to lead high-level meetings in both languages. ● Expert proficiency in Jira, Confluence, or similar project management ecosystems. Why Join Us: ● Competitive salary. ● Flexible contract types ( B2B/UoP ), work arrangements, and working hours. ● Work remotely , in-office, or from a location of your choice. ● Direct, low-bureaucracy, results-oriented culture. ● Opportunity to shape the future of conversational AI in a key scaling stage . ● Ownership and independence – we value specialists who take full accountability. ● High potential in shaping your own career path as we expand internationally.

🏢 Summary: Backend Engineer role focused on building and scaling the core architecture behind AI Agents, including reasoning layers, RAG systems, and high-volume conversational infrastructure. The position involves designing agentic orchestration, modernizing legacy systems, and integrating AI capabilities into scalable microservices running in production. You will work hands-on with LLM integrations, vector databases, and cloud-native infrastructure to support millions of daily conversations. 🗂️ Requirements: 6+ years backend development experience, Strong hands-on expertise in Node.js, Strong hands-on expertise in TypeScript, Experience with async programming, queues, and streams, Experience with real-time communication (WebSockets, service-to-service messaging), Commercial experience implementing RAG and Agentic systems in production, Experience with Function Calling and LLM integrations, Deep understanding of context management and multi-turn conversations, Experience with SQL databases (PostgreSQL), Experience with NoSQL databases (Elasticsearch), Experience with Vector Databases and embeddings, Experience with Google Cloud Platform, Experience with Kubernetes, Ability to design and maintain RESTful APIs, Experience working with microservices and scalable systems 📃 Skills: Node.js, TypeScript, PostgreSQL, Redis, Elasticsearch, Pinecone, pgvector, GCP, Kubernetes, Docker, LangGraph, LLMs, RAG, MCP, PubSub, WebSockets, SSE, Webhooks, Prometheus, Grafana, Vitest, Supertest, Playwright, Go, ETL, Microservices, Concurrency, Async, Streams, Queues, GitHubActions 🏢 Description: About your team You’ll join AI Engines – the team building the backend “brain” of AI Agents in Text App. These aren’t your average scripted bots. Our AI Agents understand context, communicate naturally, and take meaningful actions: from digging through the Knowledge Hub to answer customer queries, to guiding human agents, or triggering automations in third-party tools via Copilot. To make this happen, we need to design highly scalable backend systems capable of handling millions of conversations daily. We build the APIs, develop the reasoning layers, and continuously push the boundaries of what our agents can actually do. You will be responsible for: Hands-on building, scaling, and maintaining the core backend architecture (Vector Database, AI Engines, Knowledge Hub, etc.). Designing and implementing an Agentic reasoning and orchestration layer using Skills and tool calling (a core building block of our architecture). Modernizing the core by taking full ownership of migrating legacy implementations into our modern, highly scalable AI ecosystem. Collaborating with our AI researchers to experiment with, validate, and confidently push new AI features straight to production. Mastering Context Engineering & R&D by moving way beyond basic prompt engineering. You'll be experimenting with and optimizing how our agents communicate with LLMs (taking full ownership of multi-turn conversations, tool calling, advanced RAG integrations, system prompt design, and history management). Designing RESTful APIs and service integrations for AI and data-heavy use cases, while migrating legacy implementations to a modern ecosystem. Integrating AI Agents with MCP servers, shaping how they interact with external ecosystems. Setting the standard by taking an active part in architecture discussions, code reviews, and technical decision-making, while bringing an extreme ownership and "fast flagging" mindset to the team. You may be a good fit for this role if you: Have 6+ years of experience in backend development, with strong, recent, hands-on expertise in Node.js and TypeScript in recent projects . We need someone who is fluent in async programming, queues, and streams, and can jump into our codebase on Day 1. Have hands-on experience with real-time communication (WebSockets, async service-to-service messaging). Have proven commercial experience building AI-driven features . You don't just know the concepts—you’ve actively implemented RAG, Function Calling, and Agentic systems in production. A deep understanding of Context Engineering. You know that it’s no longer just about "writing good prompts." You have proven experience managing context windows, multi-turn conversation history, and tool calling within Agentic or RAG ecosystems. Have a solid grasp of database ecosystems, including SQL (Postgres) , NoSQL (Elasticsearch) , and Vector Databases (e.g., Pinecone, pgvector), along with the mechanics of embeddings. Know how to run and scale services on Google Cloud Platform and Kubernetes. Enjoy solving complex technical challenges in microservices, concurrency, and performance optimization. Bonus if you also: Experience with Go (Golang) is a strong plus. Have experience building Data Pipelines or ETL processes. Previous work on SaaS products, low-code/no-code platforms, or workflow automation. Our Tech Stack: (Let’s be transparent: while we value curiosity and a growth mindset, solid hands-on experience with Node.js and TypeScript is a strict requirement for this role. We are happy to give you time to learn our specific AI frameworks and databases on the go, as long as your core backend skills are top-notch.) Core (Must-have) : Node.js, TypeScript Databases : PostgreSQL, Redis, ElasticSearch Scalability & communication : PubSub, Webhooks, SSE AI-related : LLMs, LangGraph, Function Calling, Context Compression, MCP (Model Context Protocol) Infrastructure & deployment : Docker, GitHub Actions, Prometheus, Grafana Testing & reliability : Vitest, Supertest, Playwright How we work We’re a hybrid team – remote when it makes sense, onsite when it matters most. Once per quarter, your whole team spends 5 working days together at our Wrocław office – a time for focused execution, unblocking work, and driving key outcomes. Our office is open year-round – drop by anytime. Contract: B2B (self-employed). You’ll need a registered business in selected EU countries — either already set up or possible to register in your country . Please apply only if this works for you.