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 metrics 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
