We are seeking a Chief Python Developer to set technical strategy while staying hands-on across backend AI services, LLM orchestration, and agentic experiences. You will deliver production-grade code, mentor engineers, and partner with Security, Data, and Infrastructure while coordinating with US-based product and engineering peers. Help us raise the bar on observability, reliability, and operational excellence—apply now
Responsibilities
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Set technical direction for the pod and own architecture decisions within scope
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Deliver production-ready code for roughly 50%+ of your time across backend AI services, LLM orchestration, and frontend integration
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Design and build Agentic Experiences (AX) with streaming and low-latency agent UIs
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Mentor 3 Senior Engineers and 1 Data Engineer within the pod
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Collaborate daily with Security, Data, and Infrastructure teams
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Coordinate closely with US-based product and engineering colleagues
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Lead design reviews and clear blockers impacting sprint deliverables
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Maintain observability, SLOs, and reliability standards for pod services
Requirements
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Proven track record with 5+ years in software engineering, owning complex backend systems end to end
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Hands-on experience of 1–2+ years running LLM-era AI/ML platforms such as LangChain, LangGraph, or Bedrock in production; candidates with strong pre-LLM ML experience (TensorFlow, scikit-learn) who have clearly shifted to generative AI are also considered
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Expert-level Python skills for backend services and AI integration as the primary language for backend and AI work
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Practical expertise using LangChain, LangGraph, and LangSmith to orchestrate multi-step, multi-agent workflows with evaluation/observability
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Demonstrated experience delivering at production scale with AWS, Docker, and microservices
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Proficiency with GitHub Actions, ArgoCD, and OpenTofu/Terraform
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Baseline capability in secure coding practices, auth/authz awareness, and data governance
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Strong skills in API design for RESTful APIs and microservices
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English proficiency at B2 (Upper-Intermediate) level or above
Nice to have
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Strong React and TypeScript skills to contribute to UI-layer code and review frontend changes
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Awareness of MCP (Model Context Protocol) and new standards for agent interoperability
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Familiarity with AI evaluation tools such as RAGAS or custom eval frameworks
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Experience designing and tuning RAG pipelines using vector databases like Amazon Kendra and OpenSearch
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Knowledge of IAM and CIAM plus experience managing unstructured data (images, videos) with prompt context handled via LangGraph State
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
