EPAM is seeking a Houston-based AI leader to shape and deliver enterprise AI solutions for Energy and Oil & Gas clients. This role combines client advisory, AI/ML technical depth and end-to-end product delivery leadership. You will lead workshops, define AI strategy and work with engineering teams to bring high-value solutions from concept to production. Req.#[redacted] Responsibilities Partner with Energy clients and EPAM teams to define AI/ML, GenAI and agentic AI strategies, roadmaps and business cases Lead client workshops, discovery sessions and solution-design engagements with business and technical stakeholders Own end-to-end delivery of AI products, from ideation and requirements through production deployment, adoption and growth Lead multidisciplinary teams across data science, engineering, cloud, product and Energy domain SMEs Develop proposals, solution architectures and go-to-market offerings for EPAM's Energy AI practice Build team capability through mentoring, hiring and advancing AI delivery standards, reusable assets and best practices Requirements 7+ years of Data Science, ML Engineering or AI delivery experience, including 5+ years in leadership or client-facing delivery roles Strong Oil & Gas or Energy domain expertise in at least one area: Upstream, Midstream or Downstream Experience leading enterprise AI/ML programs and working directly with client executives, operational leaders and technical teams Hands-on expertise in areas such as time-series analytics, predictive maintenance, computer vision, NLP/LLMs, recommender systems or agentic AI Experience delivering production AI solutions using MLOps/LLMOps and cloud platforms such as AWS, Azure or GCP Working knowledge of Python, modern AI product SDLC practices and technologies such as Databricks, Snowflake, LangChain or Semantic Kernel Nice to have Experience in renewables, Data Center Energy Management or energy-transition initiatives Background in Oilfield Services, Energy Tech or Houston-based Energy consulting practices Experience with Energy regulatory, safety and environmental compliance requirements Cloud certifications, AI/ML publications, conference presentations or open-source contributions