AI Engineer - Gen AI & LLM & RAG

🏢 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: Senior-level role focused on building AI-driven backend applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The position involves developing scalable APIs, integrating retrieval pipelines, and deploying services in cloud environments. The role combines advanced AI implementation with solid backend engineering practices. 🗂️ Requirements: 5+ years commercial experience in Python development, Strong backend engineering experience (APIs, services, integrations), Hands-on experience with LLMs, Hands-on experience with RAG implementations, Experience with Azure, AWS, or GCP, Knowledge of software development best practices 📃 Skills: Python, LLMs, RAG, Azure, AWS, GCP, APIs 🏢 Description: Senior Python AI Developer We are looking for an experienced Python Developer to join a team building modern AI-driven applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) , alongside standard backend development work. Key Responsibilities Develop and maintain backend services and APIs in Python Build AI-enabled application features using LLMs and RAG workflows Design and integrate retrieval pipelines for contextual AI responses Work with databases, external APIs, and internal systems Deploy and operate services in Azure or other cloud environments Write clean, testable, and scalable production code Requirements 5+ years of commercial experience in Python development Strong background in backend engineering (APIs, services, integrations) Hands-on experience with LLMs and RAG implementations Cloud experience with Azure , AWS, or GCP Solid understanding of software development best practices Tech Stack Python LLMs, RAG Azure (or other cloud platforms)

🏢 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 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: 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 Fullstack Engineer role focused on delivering full-stack solutions within an AI-integrated SDLC where AI is embedded across planning, development, review, testing, and deployment. The position combines backend and frontend engineering with AI orchestration, automation, and cloud-native architecture in a remote-first setup. The engineer will also evolve shared AI toolchains and contribute to architectural and code quality standards. 🗂️ Requirements: Team-level AI-integrated SDLC experience across planning, development, review, testing, deployment, Shared AI toolchain management under version control, Hands-on use of Claude Code, GitHub Copilot, Cursor or equivalent as team tools, Building and maintaining custom AI skills and sub-agents for team use, Experience with parallel AI agent orchestration, Spec-driven development using OpenAPI, ADRs, PRDs as AI context, AI-assisted code review integrated into PR process, Working knowledge of AI orchestration frameworks, Backend development with .NET / C# and ASP.NET Core, Frontend development with TypeScript and React or Angular, Experience with SQL databases and ORM frameworks, Experience with Docker and Kubernetes, Experience with CI/CD pipelines, Experience with cloud platforms (Azure, AWS, or GCP) 📃 Skills: C#, .NET, ASP.NET, SQL, SQLServer, PostgreSQL, EFCore, OAuth, JWT, Python, Java, Node.js, TypeScript, JavaScript, React, Angular, LangChain, LlamaIndex, CrewAI, Docker, Kubernetes, GitHubActions, AzureDevOps, Azure, AWS, GCP, OpenAPI, CQRS, DDD, EventSourcing, Microservices 🏢 Description: We are looking for a Senior Fullstack Engineer who combines deep technical expertise with real, team-level experience working in an AI-integrated software development lifecycle. Individual use of AI coding assistants is not sufficient for this role. We are specifically looking for engineers who have worked in teams where AI was embedded into every phase of delivery — from planning and design through development, review, testing, and deployment. We follow a remote-first setup with no mandatory regular office visits for this position. From time to time, you may be invited to join in-person meetings in one of our offices (Warsaw, Lodz, Wroclaw, Gdansk, or Bialystok), for example for client visits or team reunions. AI-First Requirements Experience working in an AI-enabled engineering team is mandatory — not a personal workflow preference. You have been part of a team where AI was systematically embedded across all delivery phases: planning, development, review, testing, and deployment. You can speak from direct experience about how it worked, what failed, and what you would change. Specific mandatory requirements: Team-level AI-integrated SDLC experience — shared toolchain, shared configurations, shared assets under version control Hands-on with Claude Code, GitHub Copilot, Cursor, or equivalent as a team tool, not only personal usage Built and maintained custom skills and sub-agents used across a team, not just personally Experience with parallel agent orchestration for concurrent workstream execution Disciplined plan → review plan → execute approach with AI involved at every phase Maintained shared prompt libraries, skill repositories, or agent configurations in version control AI-assisted code review integrated into the PR process: CodeRabbit, Copilot review, or similar Experience with spec-driven or document-driven development where structured specifications (OpenAPI, ADRs, PRDs) serve as AI context inputs, not just human references Working knowledge of at least one AI orchestration framework: LangChain, LlamaIndex, Microsoft Agent Framework, CrewAI, or equivalent Automation-first mindset: proactively identify repetitive or inefficient parts of current work and automate them using AI and other available tools. Cost-aware AI usage: understanding how AI credits are consumed across different tools, models, and workflows, and ability to choose the most appropriate model or approach for each task. Technical Requirements Backend: .NET / C#, ASP.NET Core, SQL Server / PostgreSQL, EF Core, OAuth 2.0 / JWT. Python, Java, or Node.js is a strong plus. Frontend: TypeScript, JavaScript, React(preferable) and/or Angular, state management, async patterns, frontend testing. Architecture: Full spectrum from monolith to microservices — DDD, CQRS, Event Sourcing, event-driven design, message brokers. Infrastructure: Docker, Kubernetes, CI/CD (GitHub Actions / Azure DevOps), Azure / AWS / GCP, structured observability. Responsibilities Deliver full-stack features to a high standard of quality, performance, and reliability Contribute to architectural decisions and system design trade-offs Evolve and maintain the team's shared AI toolchain across all SDLC phases Conduct code reviews including AI-assisted tooling; uphold and enforce engineering best practices Proactively surface risks, bottlenecks, and security concerns Communicate and collaborate directly with clients in English Mentor engineers on both technical fundamentals and AI-augmented workflow practices Professional Qualities Ownership mindset · Strong written and verbal English · Comfortable in client-facing roles · Raises the AI workflow maturity of those around them

🏢 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.

🏢 Summary: Senior Full-Stack Engineer role to build a greenfield system end-to-end using Java (Spring Boot), React (TypeScript), and AWS. The position focuses on AI-augmented engineering, leveraging LLMs and agentic workflows for architecture, code generation, automation, and delivery of production-grade features. Offered as a freelance (B2B) contract. 🗂️ Requirements: Senior-level software development experience, Strong experience with Java and Spring Boot, Strong experience with React and TypeScript, Hands-on experience with AWS cloud, Experience building and operating production systems, Experience with REST APIs and relational databases, Experience with CI/CD pipelines and containers, Solid understanding of software architecture and design patterns, Practical experience using LLMs and AI coding assistants, Ability to design and run agentic AI workflows, Experience with AI-driven code generation and refactoring, Experience automating development workflows using AI tools 📃 Skills: Java, SpringBoot, React, TypeScript, AWS, REST, SQL, CICD, Docker, LLMs, AI, Git, Scrum 🏢 Description: Join us as a Full‑Stack Engineer and help shape a greenfield system end‑to‑end with Java, React, and AWS - no legacy, no shortcuts. You’ll work hands‑on with AI‑augmented engineering, using LLMs and agentic workflows to drive architecture, automate workflows, and deliver production‑grade features. This role is offered on a freelance (B2B) contract. Requirements: Senior-level experience in software development Strong experience with Java (Spring Boot) and React (TypeScript) Hands-on cloud experience (AWS) Experience building and running production systems (REST APIs, relational databases, CI/CD, containers) Solid understanding of architecture, design patterns, and trade-offs Practical experience using AI tools (LLMs, coding assistants) in day-to-day work Ownership mindset and strong problem-solving skills English level: C1 AI Tooling Fluency & Augmented Engineering We're looking for an engineer who has genuinely internalised AI into their engineering practice. Your expertise should include: Agentic Workflows & Tool Chaining: Ability to design and run multi-step AI agent workflows - from technical research, through code generation, to validation against architectural constraints. AI-Driven Architectural Research: Proficiency in using LLMs to compare frameworks, evaluate libraries, analyze RFCs and standards, and produce well-grounded architectural recommendations. AI-Driven Code Generation & Refactoring: Hands-on experience generating Java services, React components, integration tests, and migration scripts using modern AI assistants. Workflow & Tooling Automation: Building small custom tools, scripts, or MCP integrations that accelerate the team's daily work. AI Judgment: Recognizing the failure modes (hallucinations, outdated knowledge, plausible-but-wrong code) and building habits that compensate for them. Nice to have: Experience in IoT projects cloud Main responsibilities: Designing and delivering production-grade features end-to-end across Java (Spring Boot) backend and React frontend. Architectural Decisions: Driving full-stack architectural choices on a greenfield codebase - data models, API contracts, service boundaries, frontend state architecture. No legacy to hide behind. AI-Augmented Engineering: Using AI agents and LLM-based tooling daily - for technical research, evaluating libraries and design trade-offs, generating and refactoring code, debugging, and writing tests. Workflow Automation: Identifying repetitive parts of the development lifecycle (code review prep, documentation, ticket grooming, test scaffolding, release notes) and building AI-driven automations around them. Research & Decision Support: Leveraging LLMs and agentic workflows to rapidly digest technical documentation, RFCs, and vendor specs - turning hours of reading into actionable architectural input. Business Partnership: Working directly with business stakeholders - translating fuzzy requirements into clear technical scope, pushing back where it matters, and co-shaping the roadmap. Scrum & Team Dynamics: Operating in a Scrum cadence with the maturity to keep ceremonies useful and lightweight, not bureaucratic.

🏢 Summary: The offer is for a Senior Python AI Engineer to build and deploy a GenAI agent that learns from past RFP/RFI responses and accelerates new request handling. The role focuses on developing agentic AI solutions with RAG pipelines and running them reliably on AWS. You will design, implement, and maintain scalable, production-grade GenAI services within an Agile team. 🗂️ Requirements: 3+ years of Python development experience, Hands-on experience with LangChain, LangGraph or similar agent frameworks, Experience with LLM/GenAI projects, 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, Experience deploying solutions on AWS, Upper-Intermediate (B2) English or higher 📃 Skills: Python, LangChain, LangGraph, LLM, GenAI, RAG, AWS, Docker, Git, CI/CD, VectorDB, Embeddings, Prompting, Serverless, APIs 🏢 Description: We are seeking a Senior Python AI Engineer who has hands-on experience with agentic AI frameworks (LangChain, LangGraph, etc.) and knows how to run GenAI workloads on AWS. You will join the team building a GenAI agent that learns from past RFP/RFI responses and helps teams answer new requests faster. 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 functions, 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 Work within an Agile team and contribute to planning, demos, and retros Requirements 3+ years of Python development experience, with a recent focus on LLM or GenAI projects Hands-on experience with 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 Solid communication skills and the ability to work with technical and non-technical stakeholders English language proficiency at an Upper-Intermediate level (B2) or higher Nice to have Familiarity with healthcare payer workflows, especially RFP/RFI processes Experience 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.

🏢 Summary: Senior AI Software Engineer – Backend role focused on designing, building, and scaling production-grade AI backend services, including LLM integrations, RAG pipelines, and distributed cloud-native systems. The position emphasizes reliable, observable, and secure AI solutions deployed in AWS using modern backend and infrastructure practices. You will work in an Agile environment delivering scalable APIs, microservices, and AI-driven workflows for enterprise use cases. 🗂️ Requirements: Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, 6+ years backend or software engineering experience, Hands-on experience delivering AI-enabled or data-intensive backend solutions, Proficiency in at least one backend language: Python, Java, Go, Kotlin, C#, or TypeScript, Strong experience building REST APIs, microservices, and distributed systems, Experience with Python backend frameworks such as FastAPI and async programming, Experience integrating LLMs or cloud AI services with orchestration layers, Knowledge of RAG, vector search, and semantic retrieval concepts, Experience with SQL and NoSQL databases, Experience with AWS cloud services and cloud-native architectures, Experience with Terraform or infrastructure-as-code tools, Experience with Git and Agile/Scrum methodologies, Knowledge of testing, monitoring, logging, and AI evaluation practices 📃 Skills: Python, Java, Go, Kotlin, C#, TypeScript, FastAPI, REST, Microservices, LLM, RAG, Vector, SQL, NoSQL, AWS, Terraform, Git, Scrum, Kubernetes, Docker, CI/CD, Async, Serverless, Containers 🏢 Description: YOUR CONTRIBUTION Our culture is agile and collaborative, and we genuinely believe our people are some of the best with which you’ll ever work. We are looking for a skilled and passionate Senior AI Software Engineer – Backend to join our Centre of Excellence and the SWE team to design, build and scale production-grade AI services, intelligent workflows, and backend platforms that create measurable business value. YOUR “DAY-TO-DAY”: Design, develop and operate production-grade AI backend services, APIs, and event-driven components with strong focus on scalability, reliability, latency, and cost efficiency. Build and integrate capabilities based on LLMs and other AI services, including prompt orchestration, structured outputs, tool calling, and workflow automation. Develop retrieval and knowledge integration patterns such as RAG, vector search, and metadata-driven content pipelines for enterprise use cases. Participate and support Agile methods and frameworks by taking part in planning events, daily stand-ups, code reviews, and technical discussions. Collaborate closely with product, platform, frontend, DevOps, security, and data stakeholders as a valued member of a self-managing, cross-functional SWE team. Implement robust observability, evaluation and guardrails for AI solutions, including logging, tracing, monitoring, feedback loops and incident troubleshooting. Manage and optimize scalable distributed systems on the Cloud, using secure-by-design and infrastructure-as-code practices. Develop automated tests and evaluation suites to validate backend logic, model behavior, regression scenarios, and non-functional requirements. Translate product and business needs into reliable technical designs, reusable services, and maintainable integration patterns. Continuously improve architecture, developer experience, and engineering standards by contributing to best practices, reviews, and technical mentorship within the Backend community. BACKGROUND AND QUALIFICATIONS: Bachelor's Degree or higher in Computer Science, Software Engineering, Data Engineering, or related field, with appropriate professional experience. Proven work experience as a Backend Engineer or Software Engineer for 6+ years, with hands-on delivery of AI-enabled or data-intensive backend solutions. Strong experience with Agile delivery frameworks such as Scrum and modern source code management practices using Git. Knowledge of AI engineering patterns such as agentic workflows, semantic caching, prompt/version management, and human-in-the-loop controls. Strong proficiency in one or more backend languages such as Python, Java, Go, Kotlin, C#, or TypeScript, with production experience building APIs and services. Solid experience designing and operating backend services, microservices, and distributed systems, including RESTful APIs, asynchronous processing, and messaging patterns. Hands-on experience with Python-based AI/backend frameworks and service development patterns, such as FastAPI, async programming, data validation, and structured outputs. Experience integrating foundation model or cloud AI services and building reliable orchestration layers for prompts, tools, and model interactions. Good knowledge of data access patterns and storage technologies, including SQL and NoSQL databases, caching, and vector databases or semantic retrieval concepts. Experience with AWS cloud services and cloud-native engineering practices, including serverless, containers, observability, and infrastructure automation. Experience with Terraform or other infrastructure-as-code tooling. Knowledge of AI solution quality practices, including testing strategies, evaluation, monitoring, security, privacy, and responsible-use guardrails. Knowledgeable about software architecture, design patterns, logging, monitoring, and performance optimization. Excellent analytical and time management skills, strong teamwork mindset, and a pragmatic problem-solving attitude. Passionate about software engineering, continuous learning, and the practical adoption of emerging AI technologies. ADDITIONAL EXPERIENCE PREFERRED OR HELPFUL: Experience with cloud AI platforms and managed model services, preferably in AWS environments. Experience with Kubernetes, Docker containers, and CI/CD pipelines for deploying and operating AI-enabled services. Experience with product and collaboration tools such as Jira and Confluence. Summary: Senior AI Software Engineer – Backend Role in a nutshell: A senior backend engineer focused on building and scaling production-grade AI services — think LLM integrations, RAG pipelines, agentic workflows, and cloud infrastructure — within a collaborative, cross-functional team. Experience needed: 6+ years in backend/software engineering, with hands-on AI or data-intensive delivery. Must-have tech: Python (FastAPI, async), REST APIs, microservices, Terraform, AWS, SQL/NoSQL/vector databases, Git, Agile/Scrum. Nice to have: Kubernetes, Docker, CI/CD, Terraform, Jira/Confluence. Key soft skills: Strong communicator, team player, pragmatic problem-solver, passionate about AI and continuous learning. Degree: Computer Science, Software Engineering, or related field. The right candidate is someone who bridges solid backend engineering fundamentals with practical AI delivery experience — not just a data scientist or ML researcher, but an engineer who ships reliable, observable AI products in production.