Senior AI-Native Engineer

EPAM is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, they empower clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• 5+ years of experience shipping and maintaining production software, with the ability to write code, reason about architecture, debug unfamiliar systems, and explain technical decisions
• Daily experience with coding agents such as Claude Code, Codex, Cursor, or equivalents
• Understanding of agent capabilities, limitations, and failure modes
• Hands-on experience configuring and adapting agent harnesses using skills, specialized agents, hooks, and tool integrations
• Understanding of context, execution loops, state, failure recovery, and completion verification
• Capability to turn an open-ended goal into practical steps, work through blockers, and bring others along
• Capability to take responsibility for the result, including code written by an agent
• English proficiency at B2 level or higher

Nice to have:

• Experience building a coding-agent harness from scratch
• Familiarity with custom tools or MCP integrations
• Experience with agent evaluations
• Experience coordinating multiple agents

• Take a goal and make it happen: understand the problem, challenge assumptions, choose an approach, and follow through
• Deliver results that may include a production feature, a validated architecture, or an AI workflow that makes the team more effective
• Put coding agents to work to explore codebases, implement features, test, debug, and review changes
• Decide what to delegate to agents, where to intervene, and how to verify the result
• Configure and extend agent harnesses, including context, skills, specialized agents, hooks, tools, execution environments, and feedback loops
• Connect agents to real repositories and engineering workflows
• Try new approaches on real problems and measure what improves
• Help teammates adopt approaches that work across the team