Lead AI Software Engineer

EPAM Systems is seeking a Lead AI Software Engineer to embed AI-driven capabilities into the Software Development Life Cycle (SDLC) and scale their use across engineering teams. The role involves engineering integrations, automation, and enablement for LLM-based tooling across workflows like CI/CD, testing, and code review, while promoting secure and responsible practices.

Responsibilities:

• Design AI-powered solutions embedded in SDLC workflows across requirements, development, testing, and CI/CD
• Build backend services and integrations that enable LLM-based tooling in engineering environments
• Create prototypes and deliver production-grade AI-assisted automation
• Integrate AI capabilities into CI/CD pipelines, code review processes, and testing frameworks
• Identify high-impact SDLC use cases for AI enablement
• Establish best practices for AI-assisted development
• Guide engineering teams in adopting AI tools through hands-on support
• Define guardrails for secure and responsible AI usage
• Measure and report the effects of AI adoption on cycle time, quality, and productivity

Requirements:

• 5+ years of professional experience with Python, with additional exposure to Java or Node.js as a bonus
• Hands-on experience integrating external APIs, including AI/LLM services
• Solid background in CI/CD pipelines and DevOps practices
• Deep understanding of microservices architecture with familiarity in Docker and Kubernetes
• Proven track record delivering production-grade services with scalability, monitoring, and logging
• Practical experience with LLM APIs and prompt design
• Strong understanding of end-to-end SDLC processes and improving developer productivity through tooling
• Demonstrated ability to drive adoption of new technical practices and translate AI capabilities into engineering improvements
• Excellent communication skills with the ability to lead demos, workshops, and internal technical sessions
• Advanced English proficiency (B2+/C1)
• Change management experience to help drive adoption and sustain new AI-enabled engineering practices