Senior Python Developer

🏢 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: 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: The offer is for a backend-focused AI Engineer role building a modern AI platform for business process automation and multi-agent system integration in a production-grade enterprise environment. The position centers on developing scalable Python-based services, secure API integrations, and cloud-native AI solutions using LLMs and RAG. The role involves designing robust, secure, and scalable architectures deployed on AWS or Azure with containerized infrastructure. 🗂️ Requirements: Extensive experience in backend development with Python in production environments, Hands-on experience with AI Agents, RAG, MCP, or LLM-based solutions, Experience with system integrations and API architecture, Experience with scalable cloud-based applications, Experience with AWS or Azure, Experience with Docker and Kubernetes, Experience designing secure and scalable enterprise solutions, Experience with multi-agent systems and workflow automation, Ability to conduct code reviews and mentor developers, Fluent English and Polish 📃 Skills: Python, LLM, RAG, MCP, AWS, Azure, Docker, Kubernetes, API, Microservices, Cloud, AI, Agents 🏢 Description: Additional information The project focuses on building and developing a modern AI platform supporting business process automation and the integration of intelligent agents with enterprise systems. The team is creating scalable solutions based on Python, cloud technologies, and multi-agent architecture, leveraging technologies such as LLMs, RAG, and advanced workflow automation. A key aspect of the project is designing secure integrations between AI platforms, internal systems, and external APIs within a production-grade environment. The project is delivered in an international technology-driven environment with a strong focus on innovation, high-quality architecture, and the development of cutting-edge AI solutions for a global industrial organization. You’re ideal for this role if you: Have extensive experience in backend development with Python in production environments Have hands-on experience with AI technologies such as AI Agents, RAG, MCP, or LLM-based solutions Understand system integrations, API architecture, and scalable cloud-based applications Have worked with AWS or Azure and containerized environments such as Docker and Kubernetes Are experienced in designing secure and scalable enterprise solutions Have strong problem-solving skills and can proactively remove technical blockers Enjoy working closely with cross-functional teams in an international environment Have experience mentoring developers, conducting code reviews, and promoting engineering best practices Are interested in modern AI architectures, workflow automation, and multi-agent systems Communicate fluently in English and Polish and feel comfortable working in a global setup Your day-to-day responsibilities include:​ Designing and developing scalable backend services and AI-driven integration solutions in Python Building and maintaining APIs, connectors, and middleware between AI platforms and enterprise systems Creating and optimizing multi-agent workflows and intelligent automation processes Collaborating with AI Engineers, Data Engineers, and other technical stakeholders on system architecture and integrations Integrating external AI platforms, internal tools, and cloud services into production environments Working with cloud technologies and containerized infrastructure in AWS or Azure environments Improving the quality, reliability, and performance of AI-powered solutions and LLM-based workflows Conducting code reviews, mentoring team members, and supporting engineering best practices Troubleshooting technical issues, identifying bottlenecks, and driving continuous improvements Contributing to technical documentation, architecture discussions, and innovation initiatives across the team

🏢 Summary: The role involves architecting and deploying advanced AI-driven applications using Azure AI services and modern generative AI frameworks. The position focuses on building scalable knowledge retrieval systems, intelligent AI agents, and integrating AI capabilities into existing products. It requires strong expertise in cloud-native, containerized, and MLOps-driven environments. 🗂️ Requirements: Practical experience with Azure AI ecosystem, Experience with GitHub and DevOps methodologies, Strong programming skills in Python, Hands-on experience with embeddings and text chunking, Experience with vector search solutions, Experience with FastAPI and Pydantic, Experience with pymongo and Azure SDKs, Experience designing scalable AI systems, Experience building document processing pipelines, Experience with cloud-native infrastructures 📃 Skills: Azure, AzureOpenAI, AzureDocumentIntelligence, OCR, LangChain, RAG, CAG, MongoDB, PostgreSQL, Python, FastAPI, Pydantic, pymongo, Docker, GitHub, DevOps, MLOps, Embeddings, VectorSearch, JSON 🏢 Description: We are looking for a skilled AI Full-Stack Developer to architect, implement, and deploy advanced AI-driven applications. The ideal candidate will work with Azure AI services, MongoDB Atlas, LangChain-based workflows, RAG/CAG frameworks, and containerized environments (Docker), while leveraging modern AI agent technologies. Key Responsibilities Design and implement Generative AI solutions using Azure OpenAI, Azure Document Intelligence, OCR capabilities, and other Azure cloud services. Work closely with front-end and back-end teams to seamlessly embed AI functionalities into existing systems. Review and maintain high-quality code for AI service integrations, ensuring best practices and performance standards are met. Create scalable knowledge retrieval systems using LangChain, RAG/CAG approaches, and vector databases—primarily MongoDB Atlas—with working knowledge of PostgreSQL. Develop intelligent AI agents capable of autonomous reasoning, planning, and interaction with external tools. Support and promote AI-augmented development practices with tools such as GitHub Copilot or Factory AI. Requirements Practical experience with the Azure AI ecosystem, GitHub, DevOps methodologies, generative AI architectures, and vector search solutions. Strong programming skills in Python and familiarity with modern MLOps and DevOps environments. Hands-on experience with embeddings and text chunking strategies, JSON and markup formats, FastAPI, Pydantic, pymongo, and Azure SDKs. Proven expertise in designing scalable AI systems, document processing pipelines, and cloud-native infrastructures. Strong communication abilities and experience collaborating within cross-functional teams.

🏢 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

🏢 Summary: The role involves developing and maintaining backend components in Python while supporting the implementation of AI-driven features within products. The position focuses on integrating AI/ML components, working with data, and contributing to simple model development and backend services. It is suited for candidates with commercial Python experience and initial hands-on exposure to AI/ML technologies. 🗂️ Requirements: Minimum 2 years of commercial experience with Python, Hands-on experience with AI/ML features, Experience working with APIs, Experience developing backend services, Understanding of software development best practices 📃 Skills: Python, AI, ML, APIs, TensorFlow, PyTorch, scikit-learn, OpenAI, LLM, NLP, AWS, GCP, Azure 🏢 Description: We are looking for a Junior/Regular AI Engineer to join our team and support the development of AI-powered features within our products. This role is ideal for someone with solid Python skills and initial hands-on experience working with AI/ML components. Responsibilities Develop and maintain backend components using Python Support the implementation of AI-driven features and capabilities within products Collaborate with product and engineering teams to integrate AI solutions Work with data and assist in building simple ML/AI models or integrations Contribute to code quality, testing, and documentation Requirements Minimum 2 years of commercial experience with Python Initial hands-on experience with AI/ML features (e.g. working with models, APIs like OpenAI, basic ML pipelines, etc.) Understanding of software development best practices Experience working with APIs and backend services Good problem-solving skills and willingness to learn in the AI space Nice to have Experience with libraries/frameworks such as: TensorFlow, PyTorch, scikit-learn Familiarity with LLMs, NLP, or Generative AI Experience with cloud platforms (AWS, GCP, Azure) Basic knowledge of data engineering concepts We offer Opportunity to work on real AI-driven products Exposure to modern AI technologies and tools Supportive team and learning environment

🏢 Summary: The role involves developing and maintaining Python-based backend components while supporting the implementation of AI-driven features in products. The position focuses on integrating AI/ML solutions, working with data, and contributing to simple model development and backend services. It is suited for candidates with commercial Python experience and initial hands-on exposure to AI technologies. 🗂️ Requirements: Minimum 2 years commercial experience with Python, Hands-on experience with AI/ML features, Experience working with APIs, Experience developing backend services, Understanding of software development best practices 📃 Skills: Python, AI, ML, APIs, TensorFlow, PyTorch, scikit-learn, OpenAI, LLM, NLP, AWS, GCP, Azure 🏢 Description: We are looking for a Junior/Regular AI Engineer to join our team and support the development of AI-powered features within our products. This role is ideal for someone with solid Python skills and initial hands-on experience working with AI/ML components. Responsibilities Develop and maintain backend components using Python Support the implementation of AI-driven features and capabilities within products Collaborate with product and engineering teams to integrate AI solutions Work with data and assist in building simple ML/AI models or integrations Contribute to code quality, testing, and documentation Requirements Minimum 2 years of commercial experience with Python Initial hands-on experience with AI/ML features (e.g. working with models, APIs like OpenAI, basic ML pipelines, etc.) Understanding of software development best practices Experience working with APIs and backend services Good problem-solving skills and willingness to learn in the AI space Nice to have Experience with libraries/frameworks such as: TensorFlow, PyTorch, scikit-learn Familiarity with LLMs, NLP, or Generative AI Experience with cloud platforms (AWS, GCP, Azure) Basic knowledge of data engineering concepts We offer Opportunity to work on real AI-driven products Exposure to modern AI technologies and tools Supportive team and learning environment

🏢 Summary: Lead AI Software Developer role focused on architecting and scaling AI-powered applications, backend systems, and multi-agent workflows across cloud and enterprise environments. The position involves designing secure integrations, optimizing LLM-based solutions, and leading technical delivery and best practices. It combines hands-on AI development with backend architecture and technical leadership. 🗂️ Requirements: Degree in Computer Science, AI, Data Science or related field, 8+ years of software engineering experience, 5+ years of Python backend development in production, Experience building and scaling Python applications, Hands-on experience with AI Agents, RAG and MCP, Experience with AWS or Azure cloud platforms, Experience with storage systems and databases, Knowledge of containerization and Kubernetes, Experience with API integrations and enterprise system connectivity, Leadership and mentoring experience 📃 Skills: Python, AWS, Azure, Kubernetes, RAG, MCP, APIs, Cloud, Databases, Containerization, AI, LLM 🏢 Description: We are seeking an experienced Lead AI Software Developer to design and scale AI-powered applications and integrations. In this role, you will architect backend systems, lead AI agent development, and ensure secure, scalable integration across cloud platforms and enterprise systems. Key Responsibilities Design and maintain middleware, APIs, and connectors integrating AI agents with enterprise systems Architect scalable backend services and cloud-based solutions (AWS/Azure) Develop and optimize multi-agent workflows and adaptive decision logic Fine-tune prompts and LLM-based solutions for domain-specific use cases Lead code reviews, mentor developers, and define development best practices Drive complex API integrations with internal and external AI platforms (incl. MCP servers) Remove technical roadblocks and ensure timely delivery Collaborate with AI, Data, and Platform teams to optimize automation architectures Maintain technical documentation and promote continuous improvement Requirements Degree in Computer Science, AI, Data Science, or similar field 8+ years of software engineering experience, including 5+ years of Python backend development (production) Strong experience building and scaling Python applications Hands-on experience with AI technologies (AI Agents, RAG, MCP) Experience with cloud platforms (AWS or Azure), storage, databases, and AI services Knowledge of containerization and Kubernetes Experience with API integrations and enterprise system connectivity Strong leadership and mentoring experience Excellent communication skills; fluent in Polish and English (min. B2); German is a plus Willingness to travel internationally (~10%) Nice to have: Experience with LangChain, LangGraph, multi-agent systems, prompt engineering, and LLM fine-tuning. What We Offer Work in a global and innovative technology environment Direct impact on enterprise AI and automation solutions Professional development and access to training programs Hybrid work model with flexible hours (central Wroclaw office) Competitive benefits package, cafeteria system, CSR initiatives, and employee clubs

🏢 Summary: The role involves designing and building GenAI-powered services in healthcare using Python, focusing on creating RAG-based LLM agents and deploying scalable solutions on AWS. The engineer will develop, deploy and maintain AI agents with proper monitoring, guardrails and data compliance. The position requires strong full-stack and AI expertise to deliver reliable, production-ready intelligent systems. 🗂️ Requirements: 5+ years of Python or ReactJS development experience, Recent hands-on experience with LLM or GenAI projects, Hands-on expertise with LangChain, LangGraph or similar frameworks, Understanding of agentic design patterns (tools, planners, memory), Knowledge of vector databases and embeddings, Experience with prompt engineering, Proficiency with Docker, Experience with Git-based CI/CD, Experience with automated testing, Ability to deploy solutions on AWS 📃 Skills: Python, ReactJS, LangChain, LangGraph, LLM, GenAI, RAG, AWS, Docker, Git, CI/CD, Testing, Embeddings, VectorDB, Prompting 🏢 Description: We are seeking a Senior Python AI Engineer (Full Stack) to design and build intelligent GenAI-powered services that solve real business challenges in the healthcare space. In this role, you will develop Python services that power GenAI agents, create retrieval-augmented generation flows, and deploy scalable solutions on AWS while collaborating with cross-functional teams to deliver reliable and safe AI experiences. Responsibilities Build Python services that power the GenAI agent, using LangChain, LangGraph or similar libraries Create retrieval-augmented generation (RAG) flows that pull the right context and streamline LLM responses Run the solution on AWS using containers, serverless or managed AI services Instrument logging, monitoring and guardrails to keep the agent reliable and safe Ensure the ingestion and use of RFP/RFI data follows healthcare data policies Collaborate with product, data science and business teams to make sure the agent solves real problems Document code, APIs and deployment steps so others can maintain and extend the solution Contribute to planning, demos and retros within an Agile team Requirements 5+ years of experience in Python or ReactJS development, with recent focus on LLM or GenAI projects Hands-on expertise in LangChain, LangGraph or comparable agent frameworks Understanding of agentic design patterns and how to wire tools, planners and memory together Knowledge of vector databases, embeddings and prompt engineering Proficiency in Docker, Git-based CI/CD and automated testing Familiarity with AI-assisted development tools (e.g., Cursor, GitHub Copilot, Code Interpreter) to accelerate prototyping and code reviews Solid communication skills and the ability to work with technical and non-technical stakeholders Nice to have Familiarity with healthcare payer workflows, especially RFP/RFI processes Background in integrating with CRMs/workflow tools like Salesforce or ServiceNow Exposure to responsible AI, human-in-the-loop review, or safety tooling AWS or Python certifications We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.