We are building a Chief Python Developer role to set technical direction and lead hands-on delivery for backend AI services and LLM orchestration. You will write production Python, mentor engineers, and collaborate with Security, Data, and Infrastructure while aligning with US-based product and engineering partners. Help raise observability, reliability, and operational excellence across pod services—apply now.

Responsibilities

• Define technical direction for the pod and own architecture decisions within scope
• Deliver production code (~50%+ of the time) across backend AI services, LLM orchestration and frontend integration
• Design and build Agentic Experiences (AX) with streaming, low-latency agent UIs
• Coach 3 Senior Engineers and 1 Data Engineer within the pod
• Collaborate daily with Security, Data and Infrastructure teams
• Coordinate with US-based product and engineering counterparts
• Run design reviews and remove blockers to protect sprint deliverables
• Uphold observability, SLOs and reliability standards for pod services

Requirements

• Proven track record with 7+ years of software engineering experience owning complex backend systems end-to-end
• Hands-on experience of 3+ years with LLM-era AI/ML platforms such as LangChain, LangGraph or Bedrock in production; deeper pre-LLM ML backgrounds (TensorFlow, scikit-learn) with a clear recent pivot to generative AI are also considered
• Expert-level proficiency in Python for backend services and AI integration as the primary language for backend and AI work
• Deep expertise in LangChain, LangGraph and LangSmith to orchestrate multi-step, multi-agent workflows plus evaluation/observability
• Solid background running production workloads with AWS, Docker and microservices
• Practical skills with GitHub Actions, ArgoCD and OpenTofu/Terraform
• Strong understanding of secure coding practices, auth/authz awareness and data governance as default standards
• Advanced knowledge of API design including RESTful APIs and microservices
• English proficiency at B2 (Upper-Intermediate) level or higher

Nice to have

• Fluency in React and TypeScript with ability to contribute to UI-layer code and review frontend work
• Familiarity with MCP (Model Context Protocol) and emerging agent interoperability standards
• Knowledge of AI evaluation tooling such as RAGAS or custom eval frameworks
• Background designing and optimizing RAG pipelines with vector databases (Amazon Kendra, OpenSearch)
• Understanding of identity/security domains (IAM, CIAM) and working with unstructured data (images, videos) using prompt context management via LangGraph State

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn