Lead AI Engineer

About the role

EPAM is seeking a Lead AI Engineer to join its Doha office. In this senior position you will shape AI‑driven strategies, architectures and operating models, guiding engineering teams toward spec‑driven and agentic AI delivery. The role balances innovation with compliance, security and operational integrity to deliver measurable business outcomes.

Key responsibilities

• Architect and deploy token‑efficient AI search and retrieval systems optimized for cost, relevance and performance.
• Advise on AI adoption strategies, including when to apply RAG, agents, copilots or traditional engineering approaches.
• Define and implement spec‑driven development practices with governance and reusable standards.
• Design KPIs to measure productivity gains, quality improvements and AI adoption maturity.
• Build end‑to‑end AI pipelines, including embeddings, vector stores, retrieval layers, LLM integrations and streaming inference.
• Develop operational strategies for agentic systems, covering rollout governance, versioning and observability.
• Partner with product owners and engineering leads to define AI adoption roadmaps and enable workforce capability uplift.
• Drive training, playbooks and mentorship to accelerate workforce readiness in AI‑enabled engineering workflows.
• Implement responsible AI practices, ensuring compliance with security, safety and ethical guidelines.

Required profile

• Bachelor’s degree in Computer Science, Software Engineering or a related field.
• 4+ years of experience building production AI systems or 2+ years with production‑level LLM/RAG solutions.
• Proven track record leading AI transformations, strategy design and adoption initiatives.
• Deep expertise in Retrieval‑Augmented Generation (RAG) architectures, embeddings, vector databases and retrieval strategies.
• Strong proficiency in Python; familiarity with Java and API protocols (REST/gRPC).
• Experience with agent frameworks and implementing agentic workflows in enterprise software delivery.
• Practical knowledge of Kubernetes, cloud services, CI/CD pipelines and deployment automation.

Required skills

• Python
• Java
• REST
• gRPC
• Kubernetes
• Cloud Services
• CI/CD pipelines
• Deployment automation
• Embeddings
• Prompt governance
• Model versioning
• AI search and retrieval systems
• Agent frameworks
• Retrieval strategies
• Vector databases
• LLM integrations
• AI observability
• RAG architectures