Lead AI SDLC Enablement Engineer

EPAM Systems is a leading global provider of digital platform engineering and software development services. We help global brands innovate and transform their core businesses through technology.
Join us as a Lead AI SDLC Enablement Engineer to embed AI-powered tooling directly into the software development lifecycle across client organizations. This is a hands-on practitioner position at the frontier of how software is built.
You will deploy, configure and champion EPAM’s AI SDLC tooling ecosystem like EPAM DIAL and other delivery accelerators. Act as the engine of continuous improvement by evaluating emerging tools, running structured evaluations and building the playbooks that keep EPAM Systems ahead of the curve.
Responsibilities
EPAM's AI SDLC tooling portfolio mastery to understand configuration, extensibility and real-world implementation
Lead the deployment and adoption of AI SDLC tools within client engineering organizations through workflow assessment and integration point identification
Embed AI assistance across the full software development lifecycle including code generation, review, test authoring and documentation
Design and deliver structured enablement programs such as workshops, pair programming sessions and self-serve onboarding materials
Evaluate emerging AI SDLC tooling options against real delivery use cases to inform EPAM's tooling roadmap
Build and maintain a library of deployment playbooks, configuration templates and integration guides
Track adoption and impact metrics such as cycle-time reduction and developer satisfaction to demonstrate value to client stakeholders
Collaborate with EPAM's AI practice and account teams to translate capabilities into practical client proposals
Requirements
Demonstrable engineering background with strong hands-on ability across modern software delivery practices including CI/CD pipelines, code review and automated testing and agile delivery
Practical expertise with AI coding assistants and SDLC tools like GitHub Copilot, Cursor, Codeium or Amazon Q Developer within real engineering workflows
Proven capability to enable and coach engineering teams through workshops, pair programming and hands-on guidance
Analytical approach to tool evaluation, success metric definition and presentation of findings to technical and non-technical stakeholders
Strong communication practices to tailor technical content for audiences ranging from developers to executive teams
Experience to adapt quickly to different codebases, delivery methodologies and team norms across multiple client environments
Nice to have
Familiarity with EPAM DIAL or other enterprise AI assistant platforms
Experience with AI tooling integration into IDEs, CI/CD pipelines and code review workflows
Exposure to AI-assisted testing frameworks or tools for automated test generation
Background in developer experience (DevEx) or internal developer platform programs
Understanding of responsible AI and security considerations, including IP risk, code security scanning and data governance