AI Developer Enablement Lead

EPAM Systems, Inc.
United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Software as a Service Code Review Continuous Integration Cursor (Graphical User Interface Elements) Systems Development Life Cycle Software Engineering Apache OpenOffice GitHub Copilot Large Language Models Multi-Agent Systems Prompt Engineering
+1 more
Virtual Agents

Requirements

We are seeking an AI Developer Enablement Lead to drive AI adoption across engineering teams. This role operates through direct coaching, structured workshops and open office hours, building AI fluency at the team level and creating the internal champions needed to sustain L3 adoption beyond the engagement. Responsibilities Run 1:1 AI coaching sessions with engineering champions across the production teams Facilitate team-level workshops on Agentic AI Delivery Framework usage, prompt engineering and agentic workflow adoption Host recurring office hours for developers to troubleshoot, experiment and deepen AI tool fluency Deliver masterclass content in mid-June (Prompt and context engineering, BMAD for SDLC, How to build custom AI-Augmented agents and workflows) Identify and nurture internal AI champions within engineering teams Track enablement progress and report on adoption metrics (usage, workflow coverage, time saved) Collaborate with AI Coach Product/UX on cross-role enablement initiatives Create and maintain a library of Agentic AI Delivery Framework workflow examples, how-to guides and best practices for engineering Requirements 5+ years in software engineering, with recent hands-on experience using AI coding assistants (GitHub Copilot, Cursor, Codeium or equivalent) Skills in coaching, mentoring or training facilitation, with experience enabling peers or teams preferred Understanding of software development workflows (code review, CI/CD, testing, sprint rituals) Capability to explain complex AI/LLM concepts to engineers at varying experience levels Background in writing clear technical documentation and workflow guides Self-directed and comfortable in ambiguous, rapidly evolving consulting environments Proficiency in async communication for distributed team collaboration English proficiency at B2 level or higher Nice to have Familiarity with Agentic AI Delivery Framework, LangChain or CrewAI and other agent orchestration frameworks Background in developer relations, technical education or engineering coaching Experience in a high-growth SaaS engineering environment

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