Backend Engineer, AI Agent Systems

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience across frontend and backend systems, System design, distributed applications and API architecture knowledge, Experience with LLMs, RAG systems or AI-powered applications, Ability to own features from concept through production deployment, Pragmatic decision-making in ambiguous, fast-moving environments, Cross-functional collaboration with engineering, Machine Learning and product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the role This role focuses on building the product layer that turns advanced AI capabilities into useful, production-grade workflows. The engineer will design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do - Build end-to-end product functionality across frontend, backend and AI integrations. - Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. - Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. - Design real-time AI interactions involving streaming, partial results and strict latency requirements. - Improve system reliability, observability and fallback mechanisms. - Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. - Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for - Strong professional experience in full-stack engineering across frontend and backend systems. - Solid understanding of system design, distributed applications and API architecture. - Experience working with LLMs, RAG systems or other AI-powered applications. - Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. - Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. - Confidence working in a fast-moving environment with evolving product requirements. - Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like - AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. - Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. - AI interactions remain responsive and achieve low latency without compromising output quality. - Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. - The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. - Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. - The resulting product experience feels proactive, consistent and dependable to users. Technology stack - Next.js - Python - Node.js - PyTorch - OpenAI, Anthropic and open-source LLMs - SQL and NoSQL databases - Kubernetes - Docker Compensation and employment The position is offered under an employment contract. Compensation is assessed individually based on professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, and expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The organization operates remotely with globally distributed teams. There is no fixed company-wide working schedule or required time zone; team members must maintain sufficient overlap with immediate colleagues for effective collaboration. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists across different regions. Poland-based employees join existing global teams. The reporting line and hiring manager will be confirmed during the recruitment process. How the team works The role is part of a small, hands-on team where decisions are made collaboratively and individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team balances production quality, experimentation and continuous learning from real user behavior. Recruitment process The standard process includes up to four stages: - Technical assessment, where relevant to the candidate’s background. - HR interview. - One or more technical interviews. - Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on experience and previous work. Applications are evaluated by members of the technical team. Interviews may be virtual and, where relevant, onsite; the exact format and interviewers may vary.

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, external-tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience, Frontend and backend systems experience, System design expertise, Distributed applications knowledge, API architecture knowledge, LLM, RAG or AI-powered application experience, Production deployment ownership, Cross-functional collaboration with Engineering, Machine Learning and Product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product The product is an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. It must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do - Build end-to-end product functionality across frontend, backend and AI integrations. - Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. - Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. - Design real-time AI interactions involving streaming, partial results and strict latency requirements. - Improve system reliability, observability and fallback mechanisms. - Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. - Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for - Strong professional experience in full-stack engineering across frontend and backend systems. - Solid understanding of system design, distributed applications and API architecture. - Experience working with LLMs, RAG systems or other AI-powered applications. - Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. - Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. - Confidence working in a fast-moving environment with evolving product requirements. - Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like - AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. - Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. - AI interactions remain responsive and achieve low latency without compromising output quality. - Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. - The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. - Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. - The resulting product experience feels proactive, consistent and dependable to users. Technology stack - Next.js - Python - Node.js - PyTorch - OpenAI, Anthropic and open-source LLMs - SQL and NoSQL databases - Kubernetes - Docker Compensation and employment The position is offered under an employment contract. Compensation is assessed individually based on professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, and expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The organization operates as a remote-first, globally distributed team. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works Outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position; the focus is on engineers who meet the technical and ownership standards. Recruitment process The standard recruitment process consists of up to four stages: - Technical assessment, where relevant to the candidate’s background. - HR interview. - One or more technical interviews. - Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. Decisions are made efficiently, with candidates receiving a prompt outcome.

🏢 Summary: Backend Engineer role focused on building AI-centric digital products for employees and HR stakeholders. The position involves Java/Spring Boot microservices development, API and cloud integration, production observability, and maintaining secure, reliable solutions in a hybrid Kraków or Wrocław work model. 🗂️ Requirements: Strong Java and Spring Boot experience, Spring Batch and Spring Cloud experience, Microservices development experience, REST API and GraphQL schema design proficiency, NoSQL data modelling experience, Data streaming experience, OAuth 2.0 and Microsoft Entra ID knowledge, Azure Cloud Services familiarity, English communication skills, Agile collaboration experience, Commitment to quality, maintainability and documentation 📃 Skills: Java, SpringBoot, SpringBatch, SpringCloud, Microservices, REST, GraphQL, NoSQL, CosmosDB, Kafka, OAuth2, EntraID, Azure, AppServices, AzureMonitor, APIManagement, Observability, Testing 🏢 Description: Role Summary We are looking for a Backend Engineer to design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. Work Mode Hybrid (2–3 days/week) — Kraków or Wrocław office Primary Skills Java, Spring Boot, microservices, REST APIs Key Responsibilities • Design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. • Apply modern engineering practices, from analyzing user needs and developing new features to automated testing, deployment, and observability. • Ensure quality, security, reliability, and compliance by applying digital principles and implementing functional and non-functional requirements. • Build observability into solutions, monitor production health, help resolve incidents, and remediate root causes of risks and issues. • Advocate for user and stakeholder needs, ensuring AI solutions are explainable, ethical, and human-centric. • Share knowledge openly, contribute to hiring and onboarding, and help shape a collaborative, forward-thinking engineering culture. Required Skills and Experience • Strong experience in Java and Spring Boot, including Spring Batch and Spring Cloud, and building microservices. • Proficiency in REST API and GraphQL schema design. • Experience with NoSQL data modelling, such as Azure Cosmos DB; data streaming, such as Confluent Kafka; and authentication/authorization protocols, including OAuth 2.0 and Microsoft Entra ID. • Familiarity with Azure Cloud Services, including App Services, Azure Monitor, and API Management. • Collaborative communication skills: able to express ideas clearly in English and adapt technical content for diverse audiences while working closely with product managers, designers, and engineers in agile settings. • Strong commitment to quality, maintainability, documentation, and continuous learning. • AI-related skills, such as Spring AI or LangChain, are a strong plus. Benefits • Stable long-term cooperation with opportunity for extension. • Opportunity to work with modern technologies in an international environment. • Professional growth and continuous development opportunities. • Participation in challenging and impactful projects.

🏢 Summary: Backend Engineer role focused on building and operating the AI inference and orchestration layer for production mobile and desktop features. The position emphasizes reliable multi-step AI workflows, low-latency/high-throughput performance, and end-to-end operational ownership of high-traffic APIs. 🗂️ Requirements: Proven experience building and operating high-throughput, low-latency production backend services, Practical experience with AI inference patterns, including LLMs, embeddings, or multimodal systems, Experience integrating OpenAI, Anthropic, or open-source models, Ability to debug distributed backend architectures under heavy load, Experience owning production systems, metrics, monitoring, and incident response 📃 Skills: Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, Embeddings, SQL, NoSQL, Kubernetes, Docker 🏢 Description: Our client is seeking a high-caliber Backend Engineer to own the critical inference and orchestration layer that powers every single AI interaction in the platform. You’ll sit right between state-of-the-art models and millions of user interactions, where latency, correctness, and absolute reliability determine product success. What You’ll Be Doing Inference & Orchestration: Design, build, and scale the core orchestration layers, service boundaries, and inference pipelines that serve production AI features across mobile and desktop apps. Tame Non-Deterministic AI: Build high-reliability, long-running workflows that handle multi-step reasoning, external tool interaction, and persistent context despite non-deterministic model behavior. Performance Optimization: Drive low-latency and high-throughput across inference, caching, batching, and streaming strategies. Production Excellence: Own end-to-end operational quality—from monitoring, logging, and alerting to rapid incident response for high-traffic API endpoints. What We’re Looking For Solid Backend Fundamentals: Proven track record building and operating high-throughput, low-latency production services. AI/LLM Familiarity: Practical experience with AI inference patterns (LLMs, embeddings, multimodal systems) and integrating providers like OpenAI, Anthropic, or open-source models. Distributed Systems Mastery: Comfortable debugging distributed backend architectures under heavy load. Product-Minded Execution: A strong bias toward shipping fast, learning from production metrics, and taking full ownership of your systems. Tech Stack Languages: Python, Node.js AI/ML: PyTorch, OpenAI / Anthropic APIs, Open-Source LLMs Data: SQL & NoSQL databases Infra & Ops: Kubernetes, Docker, modern cloud architecture

🏢 Summary: Lead a hands-on full-stack/backend engineering effort to build scalable services, APIs, workflow engines, and agentic AI systems for logistics optimization. The role combines technical leadership, production reliability, third-party integrations, and mentoring while delivering AI-driven planning and optimization capabilities. 🗂️ Requirements: Senior or technical-lead backend engineering experience, Strong Python and API-development proficiency, Scalable distributed-systems architecture experience, API design, data modeling, and integration expertise, Agentic AI, LLM orchestration, RAG, or multi-agent systems experience, Cloud-platform and CI/CD experience, Third-party API integration experience, Production debugging experience with LLM-driven systems, Engineering mentorship and code/design review experience, Technical leadership and stakeholder communication skills, Successful pre-employment screening 📃 Skills: Python, FastAPI, TypeScript, LangGraph, LangChain, RAG, AWS, Bedrock, GitLab, CICD, SSE, WebSockets, LLM 🏢 Description: What's the role? We are looking for a Tech Lead Fullstack Engineer to build core backend systems powering next-generation agentic AI solutions for the logistics industry. The systems developed by this team optimize deliveries at scale improving driver efficiency, increasing reliability, reducing operational costs, and lowering environmental impact. In this role, you will focus on building the core service layer, customer-facing APIs, workflow engines, and integrations with HERE APIs and third-party systems that enable intelligent logistics workflows. You will work closely with senior engineers and technical leaders to design and implement scalable, reliable systems that support AI-driven planning and optimization use cases. This is a hands-on engineering role with a strong focus on backend development, system reliability, and production-quality delivery . What You’ll Do: Lead the design, build, and maintenance of core backend services, APIs, and workflow orchestration systems for logistics applications Drive integrations with HERE APIs and external third-party systems to support real-world logistics workflows Translate ambiguous product and technical requirements into scalable, maintainable system components, and help others on the team do the same Write clean, efficient, and well-tested code in Python and/or TypeScript, setting the standard for code quality across the team Design and build agentic AI systems based on LangGraph, and help shape how the team approaches LLM orchestration and multi-agent architecture Lead system design discussions and own key architectural decisions, ensuring solutions align with the overall system vision Build and maintain customer-facing APIs with a strong focus on usability, performance, and reliability Ensure high-quality delivery through testing, monitoring, and debugging in production environments, including systems with non-deterministic (LLM-driven) behavior Mentor engineers through code review, design feedback, and pairing, and help grow the team's technical capabilities Collaborate with engineers, product managers, and domain experts to deliver end-to-end features Continuously improve system performance, scalability, and operational efficiency Leverage AI-assisted development tools to improve development speed and code quality Who are you? What We’re Looking For: Proven experience as a technical lead or in a senior engineering role, with strong backend development skills and a track record of owning systems end-to-end Strong proficiency in Python, with experience building APIs (FastAPI or similar) and backend systems; TypeScript is a plus Experience architecting scalable services and distributed systems, and making tradeoff decisions that hold up under real-world load and change Strong command of API design, data modeling, and system integration patterns — ideally including streaming/event-driven APIs (e.g., SSE, websockets), not just request/response Hands-on experience building or leading development of agentic AI systems: LLM orchestration frameworks (e.g., LangGraph, LangChain), RAG pipelines, or multi-agent architectures Experience working with cloud platforms, ideally AWS (including managed LLM services like Bedrock), and modern CI/CD practices (GitLab CI or equivalent) Experience integrating with external/third-party APIs and handling real-world data and system constraints in production Strong debugging and problem-solving skills in production environments, including systems with non-deterministic (LLM-driven) components Experience mentoring engineers, conducting code/design reviews, and raising the technical bar across a team Ability to break down ambiguous problems into well-defined work, balancing hands-on coding with technical leadership Excellent communication skills, with the ability to align engineering decisions with product and business priorities, and a pragmatic approach to engineering challengesWe are looking for a Lead Software Engineer to build core backend systems powering next-generation agentic AI solutions for the logistics industry. The systems developed by this team optimize deliveries at scale improving driver efficiency, increasing reliability, reducing operational costs, and lowering environmental impact.Design , build, and maintain What We Offer: The opportunity to tackle meaningful and challenging problems A chance to continuously learn and stay on top of the latest technology trends Work that has real-world impact, shaping the future of mobility and technology Regular feedback to help you grow and succeed in your role A collaborative and supportive team environment where your contributions are valued Competitive salary plus bonus Flexible working hours and a hybrid working environment Medical coverage for you and your family This role is eligible for Creative Tax Incentive scheme in Poland” or KUP (Autorskie Koszty Uzyskania Przychodu) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case) Change is HERE. Apply Now! #LI-AK8   #LI-HYBRID Life at HERE in Poland comes with a competitive total rewards package designed to support your health, wellbeing, and performance. This includes a base salary, a Short-Term Incentive (STI) bonus (percentage based on role), a creative tax advantage for eligible positions, private medical care (including dental), life insurance, a meal allowance, vision reimbursement, a remote work allowance (if applicable), access to MyBenefit and Multisport programs, and various wellbeing initiatives. Paid time off, sick leave, and parental leave are provided in accordance with the Polish Labor Code. As part of HERE Technologies employment process, candidates will be required to successfully complete a pre-employment screening process. This offer and any related claims are subject to the successful completion of a pre-employment screening. This will involve employment, education, and criminal verification if applicable. HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics. Who are we? HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely. At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel. Apply for this job online Email this job to a friend Share on your newsfeed Connect With Us! Not ready to apply? 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🏢 Summary: Java Backend Engineer role focused on building AI-driven digital products for employees and HR stakeholders. The position covers end-to-end microservice development, testing, deployment, observability, production support, and secure, ethical AI delivery in an agile environment. 🗂️ Requirements: Strong Java and Spring Boot experience, Experience building microservices, Spring Batch and Spring Cloud experience, REST API and GraphQL schema design proficiency, NoSQL data modelling experience, Data streaming experience, OAuth 2.0 and Microsoft Entra ID authentication/authorization experience, Azure Cloud Services experience, English communication skills for cross-functional agile collaboration, Commitment to quality, maintainability, documentation, and continuous learning 📃 Skills: Java, SpringBoot, SpringBatch, SpringCloud, Microservices, REST, GraphQL, NoSQL, CosmosDB, Kafka, OAuth2, EntraID, Azure, AppServices, AzureMonitor, APIManagement, Observability 🏢 Description: Role Summary We are looking for a Java Backend Engineer to design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. Required Skills & Experience Strong experience in Java and Spring Boot, including Spring Batch and Spring Cloud, and building microservices. Proficiency in REST API and GraphQL schema design. Experience with NoSQL data modelling (e.g., Azure Cosmos DB), data streaming (e.g., Confluent Kafka), and authentication/authorization protocols including OAuth 2.0 and Microsoft Entra ID. Familiarity with Azure Cloud Services, including App Services, Azure Monitor, and API-Management. Collaborative communication skills: able to express ideas clearly in English and adapt technical content for diverse audiences while working closely with product managers, designers, and engineers in agile settings. Strong commitment to quality, maintainability, documentation, and continuous learning. Key Responsibilities Design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. Apply modern engineering practices, from analyzing user needs and developing new features to automated testing, deployment, and observability. Ensure quality, security, reliability, and compliance by applying digital principles and implementing functional and non-functional requirements. Build observability into solutions, monitor production health, help resolve incidents, and remediate root causes of risks and issues. Advocate for user and stakeholder needs, ensuring AI solutions are explainable, ethical, and human-centric. Share knowledge openly, contribute to hiring and onboarding, and help shape a collaborative, forward-thinking engineering culture.