Senior Data Scientist (AI Engineering Focus)

🏢 Summary: Opportunity to join a newly formed AI team in the banking sector to build a modern AI-native platform from scratch. The role focuses on designing and delivering production-grade solutions using LLMs, RAG, and agent-based architectures, while shaping AI strategy and architectural decisions. You will develop secure, transparent, and scalable AI systems that drive real business value in a regulated financial environment. 🗂️ Requirements: At least 3 years of experience in AI/ML, Minimum 5 years of experience in product development, Strong Python skills, Hands-on experience with LLMs, RAG, and agent-based systems in production, Experience with AI frameworks such as Agno, LangChain, LlamaIndex or similar, Knowledge of prompt engineering and AI model evaluation, Experience with Azure or AWS, Understanding of vector databases and embeddings, Experience with workflow orchestration tools (Temporal, Prefect, Airflow), Ability to design scalable and reliable AI solutions, Experience in model monitoring and MLOps practices, Ability to make architectural decisions and assess business value of AI, Fluent English 📃 Skills: Python, LLM, RAG, LangChain, LlamaIndex, Agno, Azure, AWS, Temporal, Prefect, Airflow, MLOps, Embeddings, VectorDB 🏢 Description: We are looking for an experienced Senior AI Engineer to join a newly formed AI team delivering a strategic initiative in the banking sector. This is a unique opportunity to co-create a modern AI-native platform from scratch and influence the direction of AI within the organisation. In this role, you will design and develop solutions based on LLMs, RAG systems, and agent-based architectures to support data integration and transformation processes. You will contribute to key decisions around AI strategy, model selection, architecture, and quality standards. We are seeking a candidate with strong technical skills and hands-on experience in building production-grade AI solutions—someone who understands where AI brings real business value and can deliver high-quality, transparent, and secure solutions in a financial environment. Your tasks Design and develop solutions based on LLMs, RAG, and agent-based architectures Co-create and execute an AI strategy for a modern banking platform Select models, frameworks, and approaches for production-grade AI solutions Build systems for data integration, transformation, and validation automation Define prompt engineering, model evaluation, and AI quality standards Develop monitoring, evaluation, and continuous improvement mechanisms Collaborate with engineering and product teams on new features Ensure high quality, transparency, and auditability of AI outputs Contribute to key architectural decisions and AI direction Mentor and share knowledge within the AI team Requirements At least 3 years in AI/ML and a minimum of 5 years in product development Strong Python skills Hands-on experience with LLMs, RAG, and agent-based systems in production Familiarity with frameworks such as Agno, LangChain, LlamaIndex, or similar Knowledge of prompt engineering and AI model evaluation Experience with Azure or AWS Understanding of vector databases and embeddings Experience with workflow orchestration tools (e.g., Temporal, Prefect, Airflow) Ability to design scalable, reliable AI solutions Experience in model monitoring and MLOps practices Capability to make architectural decisions and assess the business value of AI Strong collaboration skills with technical and business stakeholders Fluent English Nice-to-have requirements Previous work in financial services, fintech, or other regulated industries Knowledge of compliance, auditability, and AI security Familiarity with MLOps and large-scale ML/LLM deployments Experience fine-tuning open-source models for specific domains Proven track record in developing AI solutions for data platforms, analytics, or SaaS products Background in AI R&D projects Publications, conference speaking, or open-source contributions Experience building and scaling technical teams What we offer Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022 Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more Comfortable workplace – class A offices or remote work Dozens of fascinating projects for prestigious brands from all over the world PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers Investment in your growth – meetups, webinars, training platform and technology blog – you choose Fantastic atmosphere created by all Sii Power People If you want to work on systems with high operational significance — apply now!

🏢 Summary: Senior Machine Learning Engineer role focused on designing, developing, and deploying advanced AI models across NLP-driven document intelligence and predictive analytics initiatives. The position covers the full ML lifecycle, including LLM pipeline design, forecasting and optimization models, and production-grade MLOps in secure on-premise environments. The role operates within an agile framework with strong emphasis on robustness, explainability, and scalable deployment. 🗂️ Requirements: 5+ years of Machine Learning Engineering experience, Proven experience deploying ML models to production, Expert-level Python proficiency, Hands-on experience with PyTorch, TensorFlow, Scikit-learn, Strong experience with transformer architectures (BERT, GPT, Llama), Experience with NLP frameworks such as Hugging Face or LangChain, Experience with Docker and Kubernetes, Experience with MLflow or similar MLOps tools, Experience building data preprocessing pipelines for structured and unstructured data, Experience designing time-series forecasting models, Experience building classification and anomaly detection models, Ability to implement optimization algorithms, Experience working in agile environments 📃 Skills: Python, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, BERT, GPT, Llama, HuggingFace, LangChain, Docker, Kubernetes, MLflow, Kubeflow, SQL, NLP, LLM, RAG 🏢 Description: N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact. We are looking for a Senior Machine Learning Engineer to lead the development and deployment of advanced AI models. In this role, you will be responsible for the end-to-end lifecycle of our machine learning systems, from architectural design and data preprocessing to model training, optimization, and production deployment. You will work at the intersection of generative AI and traditional machine learning, building the engines that power two strategic AI initiatives spanning NLP-based document intelligence and predictive analytics. Operating within a structured agile delivery model with formal review gates, you will ensure our models are not just accurate, but also robust, explainable, and deployable within highly secure, on-premise environments. Key Responsibilities: LLM and NLP Pipelines Design and fine-tune Large Language Model (LLM) pipelines to interpret complex regulatory texts (e.g. standards, building codes) and extract structured rules. Convert natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by downstream compliance engines. Implement RAG (Retrieval-Augmented Generation) architectures to enable semantic querying of technical documentation and historical project data. Optimize prompt strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining. Predictive and Analytical Models (Supply Chain) Develop time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals. Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors. Design algorithms for multi-objective optimization(e.g., balancing cost vs. lead time vs. risk) to support procurement decision-making. MLOps and Productionization Containerize models using Docker/Kubernetes and deploy them into secure, on-premise inference environments. Build automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability. Optimize model inference latency and resource usage (e.g., quantization, distillation) to run efficiently on available hardware. Implement monitoring systems to track model drift and performance in production, establishing feedback loops for continuous improvement. Requirements: 5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments. Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy). Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain). Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow). Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data. Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations. Ability to quickly learn and apply ML techniques to specialized domains like engineering, supply chain, or other highly regulated industries. Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements. Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.

🏢 Summary: Senior Software Engineer role focused on designing and developing a robust Kotlin-based framework for configuring and managing AI agents. The position involves building a scalable, high-performance platform using reactive and distributed system principles. The engineer will ensure code quality, optimize performance, and maintain technical documentation. 🗂️ Requirements: 5+ years experience with Kotlin or Java, Strong experience with Spring Framework, Experience with reactive programming (Project Reactor), Knowledge of REST, GraphQL, gRPC, Experience with distributed systems, Experience with tracing, metrics, monitoring practices, Experience building frameworks or platforms, Proficiency with Maven or similar build tools, Experience with NoSQL databases 📃 Skills: Kotlin, Java, Spring, Reactor, REST, GraphQL, gRPC, DistributedSystems, Maven, NoSQL, Tracing, Monitoring, Metrics 🏢 Description: N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world. We are looking for talented Senior Software Engineer to join our AI project in Europe. Responsibilities: Design and develop a robust and extensible Kotlin framework and platform for configuring and managing AI agents Write clean, maintainable, and efficient code that complies with our coding standards Ensure the performance, quality, and responsiveness of the framework/platform Identify and correct bottlenecks and errors Help to maintain code quality, organization, and automatization. Create and maintain technical documentation for the framework/platform Requirements: At least 5 years of proficiency in Kotlin or Java Deep experience with the Spring Framework Reactive tools experience (Project Reactor) Knowledge of different communication protocols such as REST, GraphQL, gRPC Experience with distributed systems Familiarity with tracing, metrics and monitoring best practices Experience of creating frameworks and platform for other developers Proficiency in Maven or similar tools Familiarity with NoSQL databases Very good spoken and written knowledge of English language (C1) Nice to have: Familiarity with GenAI, AI agents, machine learning, and natural language processing concepts is a plus Experience with MCP, A2A, RAG is a big plus Experience with event-driven architecture Experience with Docker and Kubernetes Python experience is nice to have BSc or MSc in Computer Science, Engineering or relevant field

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI systems, including agentic workflows and RAG pipelines integrated into enterprise platforms. The position emphasizes backend engineering, API integrations, and orchestration of LLM capabilities in secure, scalable cloud environments rather than ML research. The role also includes mentoring engineers and establishing best practices for reliable, observable AI services. 🗂️ Requirements: 5+ years professional software development experience, Proficiency in Python, Experience building production LLM applications, Hands-on experience with RAG systems, Experience designing and integrating RESTful APIs, Strong understanding of distributed systems fundamentals, Experience with SQL databases and performance optimization, Experience with vector search, Experience integrating external services via APIs, Knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Microservices, DistributedSystems, Concurrency, AsyncIO, VectorSearch, Embeddings, Caching, AzureFunctions, Storage, KeyVault, AppConfiguration, ApplicationInsights, ServiceBus, EventHubs 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI solutions, including agentic workflows and RAG pipelines integrated into enterprise systems. The position emphasizes software engineering excellence, cloud-based AI services, and orchestration of LLM capabilities rather than model research. You will build reliable, secure, and observable AI services integrated with internal platforms and APIs. 🗂️ Requirements: 5+ years of professional software development experience, Strong background in designing and operating production systems, Proficiency in Python or another backend language for AI systems, Experience building and integrating RESTful APIs, Understanding of distributed systems fundamentals, Experience with API integrations and event-driven architectures, Solid SQL and database design knowledge, Experience with vector search, Hands-on experience building end-to-end LLM applications, Experience implementing RAG pipelines, Strong knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and regression testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Embeddings, VectorSearch, AzureFunctions, AzureStorage, KeyVault, AppConfiguration, ApplicationInsights 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 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: Senior-level role focused on designing and delivering scalable AI/ML solutions, including LLMs, RAG, and agent-based systems, from architecture to production deployment. The position involves leading technical decisions, writing high-quality Python code, and building cloud-based microservices solutions. The role also requires translating business needs into robust, production-ready AI systems. 🗂️ Requirements: Several years of software development experience (senior-level), Strong Python proficiency, Solid understanding of ML/AI ecosystem (LLMs, NLP, deep learning), Hands-on experience with RAG, prompt engineering, agent-based systems, Experience with microservices architecture, Experience with databases, Experience with Kubernetes, Experience with CI/CD pipelines, Experience with Azure cloud, English proficiency 📃 Skills: Python, LLMs, RAG, NLP, DeepLearning, PromptEngineering, Microservices, Databases, Kubernetes, CICD, Azure, GCP, Java 🏢 Description: Responsibilities: Design and develop scalable AI/ML solutions (LLMs, RAG, agentic systems) Write high-quality, testable Python code Lead technical architecture and make key design decisions for critical projects Own end-to-end delivery of solutions, from design to production deployment Collaborate with business stakeholders and translate requirements into technical solutions Requirements: Several years of experience as a software developer (senior-level preferred) Very strong Python skills and solid understanding of the ML/AI ecosystem (LLMs, NLP, deep learning) Hands-on experience with RAG, prompt engineering, and agent-based systems Experience with microservices architecture, databases, Kubernetes, and CI/CD pipelines Experience with Azure cloud (GCP as a plus) Basic familiarity with Java is a plus Strong English communication skills

🏢 Summary: Senior Front-End Engineer role focused on building core components of an AI-powered document processing and workflow automation platform for a global financial services organization. The position combines strong React/TypeScript front-end development with full-stack integration in a cloud-native environment. You will contribute to architecture, performance, security, and integration with AI-driven services. 🗂️ Requirements: 6+ years software engineering experience with strong front-end focus, Strong proficiency in React and TypeScript, Solid understanding of front-end architecture and state management, Experience integrating REST APIs, microservices, or event-driven systems, Experience with relational or NoSQL databases, Experience with cloud platforms (GCP, AWS, or Azure), Familiarity with CI/CD pipelines and Docker, Experience with Git and modern DevOps tools, Understanding of performance, scalability, and security principles, Experience working in agile cross-functional teams 📃 Skills: React, TypeScript, JavaScript, HTML, CSS, REST, Microservices, Python, FastAPI, Flask, Django, PostgreSQL, MySQL, MongoDB, Firestore, GCP, AWS, Azure, Docker, Git, CI/CD, PubSub, WebSockets, OAuth2, JWT, IAM, VertexAI, Gemini, LangChain 🏢 Description: (4579) N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact. Position Overview: Our client is a global UK-based financial services and investment banking organization developing an AI-powered document processing and automation platform used across multiple business units. The platform enables large-scale data processing, workflow automation, intelligent document recognition, and modern digital experiences for internal consumers across the banking group. We are looking for a Senior Front-End Engineer with solid full-stack capability to join a cross-functional engineering team building core components of the AI-driven document processing automation platform Key Responsibilities Build modern UI components and front-end features using React and TypeScript Develop reusable component libraries, design systems, hooks, and state management patterns. Work with product and design teams to translate workflows into high-quality user experiences. Integrate UIs with backend APIs, real-time events, and AI-driven document workflows. Ensure front-end performance, accessibility, responsiveness, and frontend security best practices. Collaborate with GenAI engineering teams to integrate document-processing functionality. Work with Google Cloud services such as Cloud Run, Cloud Functions, Pub/Sub, Cloud Storage. Participate in architectural discussions and technical decision-making across the platform. Write automated tests and contribute to CI/CD, code quality, and secure development practices. Requirements 6+ years of experience in software engineering with significant front-end focus. Strong proficiency in React and TypeScript Solid understanding of front-end architecture, state management, component lifecycles, and rendering models. Experience in consuming and integrating REST APIs, microservices, or event-driven systems. Experience with Python frameworks is a strong plus (FastAPI, Flask, Django). Experience with relational and/or NoSQL databases (PostgreSQL, MySQL, MongoDB, Firestore). Experience with cloud-native environments (GCP preferred; AWS/Azure acceptable). Familiarity with CI/CD pipelines, Docker, Git, and modern DevOps tooling. Strong software engineering principles: reliability, scalability, performance, security. Experience working in agile cross-functional teams on complex, multi-team products. Strong communication skills for working with technical and non-technical stakeholders. Nice to Have Experience integrating with AI/ML or GenAI-driven features. Experience with Vertex AI, Gemini, LangChain, or LLM-based services. Familiarity with event-driven systems, WebSockets, or Pub/Sub. Experience building internal tools, dashboards, or workflow automation systems. Knowledge of authentication and authorization standards (OAuth2, JWT, SSO, IAM). Understanding of OCR, document processing, or enterprise workflow products.

🏢 Summary: Senior AI Engineer role focused on building and deploying production-grade AI solutions using Python, FastAPI, Azure, Generative AI, RAG, and agentic frameworks in a hybrid work model. The position includes backend architecture, AI pipeline development, MLOps ownership, and mentoring responsibilities. 🗂️ Requirements: 6–10 years of software engineering experience, Strong AI/ML engineering background, Expertise in Python, Expertise in FastAPI, Experience with LLMs, Experience with RAG pipelines, Experience with vector databases, Hands-on experience with agentic AI frameworks, Production experience with Azure cloud services, Knowledge of MLOps, Experience with Docker, Experience with Kubernetes, Experience with CI/CD 📃 Skills: Python, FastAPI, Azure, LLMs, RAG, Pinecone, Milvus, LangChain, LangGraph, AutoGen, CrewAI, Docker, Kubernetes, CI/CD, MLOps, AKS 🏢 Description: Location: Wroclaw, Poland (Hybrid: 3 days/week in-office) Experience: 6–10 years About the Role We are looking for a Senior AI Engineer to design, develop, and deploy production-grade AI solutions using Python, FastAPI, and Azure, with a strong focus on Generative AI, LLMs, RAG, and agentic frameworks. Key Responsibilities Architect and implement scalable backend services with Python and FastAPI . Build and optimize RAG pipelines using vector databases (e.g., Pinecone, Milvus, Azure Cognitive Search). Develop autonomous agents using agentic AI frameworks (LangChain, LangGraph, AutoGen). Deploy and manage AI workloads on Azure (Azure ML, AKS, OpenAI Service). Own the full ML lifecycle: experimentation, versioning, CI/CD, and monitoring. Mentor junior engineers and drive technical best practices. Required Skills 6–10 years of software engineering experience, with strong focus on AI/ML. Expert in Python and FastAPI . Deep experience with LLMs , RAG , and vector databases . Hands-on experience with agentic frameworks (LangChain, CrewAI, etc.). Production experience with Azure cloud services. Strong understanding of MLOps, containerization (Docker/Kubernetes), and CI/CD.

🏢 Summary: The role involves owning and operating LLM inference platforms in production, focusing on API integration, orchestration, and reliability within Kubernetes-based environments. You will ensure high availability, performance, and security of inference services while managing deployments and monitoring across cloud or hybrid infrastructure. The position includes hands-on work with multi-turn conversational AI systems and production-grade observability and DevOps practices. 🗂️ Requirements: 5+ years of Python programming experience, Strong Kubernetes experience including deployment, scaling, and monitoring, Experience with production logs, monitoring, and observability systems, Understanding of LLM fundamentals and model behavior, Experience integrating and working with LLM Inference APIs (e.g., OpenAI, Anthropic), Ability to independently own and operate inference services, Solid Linux fundamentals, Experience with CI/CD workflows and Git, Knowledge of platform security and CVE monitoring 📃 Skills: Python, Kubernetes, LLM, OpenAI, Anthropic, API, Linux, Helm, ArgoCD, Git, CI/CD, Monitoring, Observability, Logs, Cloud, Rust 🏢 Description: N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact. We are looking for an Inference Platform Engineer (LLM & Kubernetes) to join our team. Our client is a leading European AI company developing large language models and generative platforms for enterprise and government clients. Their products combine high-performance technologies, transparency, accessibility, and data security, fully aligned with European regulatory and ethical standards. As an Inference Platform Engineer (LLM & Kubernetes) , you will take ownership of inference API integration, operations, and platform reliability across production AI systems. This role is designed to be covered by 1–2 FTE split across several senior specialists , ensuring continuity of inference services and full coverage during planned and unplanned absences as we take over end-to-end LLM inference responsibility. Responsibilities: Take ownership of inference API integration, orchestration, and long-term platform reliability Lead operations for LLM inference services as they transition under internal ownership Ensure inference API availability, latency, and performance in production environments Design and maintain multi-turn conversation handling, chat templates, and prompt orchestration Proactively monitor, troubleshoot, and resolve inference platform issues, logs, and errors Manage Kubernetes deployments, Helm charts, and ArgoCD workflows for inference services Ensure platform security, CVE monitoring, and compliance with internal and regulatory standards Collaborate closely with backend, platform, and infrastructure teams Maintain clear operational documentation to support shared ownership across multiple FTEs Participate in support / on-call rotation as required to ensure operational continuity Requirements: 5+ years of Python programming experience Strong Kubernetes (k8s) experience, including deployment, scaling, and monitoring Experience handling large-scale logs, monitoring, and observability in production Basic knowledge of LLM fundamentals and the surrounding industry  (e.g., what type of models exist, how does an LLM generate output) Experience from the user side developing against an Inference API (e.g., OpenAI, Anthropic, OpenRouter etc.) and understanding  of their structure (experience with providing or deploying a similar API yourself a strong plus) Ability to independently own and operate inference services in a shared-responsibility model (1–2 FTE split across multiple specialists) Strong communication skills and experience working with cross-functional engineering teams Solid Linux fundamentals Nice to have: Hands-on experience with Helm charts, ArgoCD, and CI/CD for AI services Interest in partly working with Rust Senior-level experience with production LLM inference or AI platform operations Experience building or operating multi-turn conversational AI systems Familiarity with real-time API orchestration or streaming inference workloads Background in MLOps, AI platform engineering, or SRE Experience with cloud-based inference deployments and scaling Knowledge of security, CVE scanning, and operational best practices Technology Stack: Inference: OpenAI, Anthropic, or other LLM inference APIs Focus Areas: API integration, multi-turn conversation orchestration, tool calling, platform reliability Infrastructure: Kubernetes, Helm, ArgoCD, cloud or hybrid environments Monitoring: Logs, metrics, observability tools for inference systems Workflow: Git, CI/CD pipelines, documentation, operational runbooks, incident handling Standards: Reliability, latency, performance, security, maintainability