What are the responsibilities and job description for the Google Agentic AI Architect position at EPAM Systems?
EPAM is seeking an ML and AI Projects Delivery leader specializing in Google Cloud's Generative AI ecosystem, with a focus on Gemini Enterprise. This role leads our most advanced AI engagements - combining deep LLM expertise with proven program and delivery management - while driving pre-sales, RFP responses, and architectural oversight for enterprise-scale Gemini deployments. Req# Responsibilities Build architecture visions and technology roadmaps centered on Gemini Enterprise and the broader Google Cloud Platform AI ecosystem Proven experience as a Technical Consultant, successfully leading both pre-sales engagements and end-to-end project delivery Lead and oversee complex ADK (Agent Development Kit) deployments, ensuring scalable, secure, production-ready environments Partner with client executives on enterprise AI platform builds and Generative AI transformations Drive pre-sales activities/business development - client demos, architectural proposals, and RFP/RFQ/RFI responses focused on GenAI strategy Lead engagement kickoff, establishing program governance, success metrics, and managing complex GenAI delivery programs Accountable for driving business development opportunities, partner interaction, pre-sale activities, and RFPs to help EPAM win new business in ML and AI domains Design and facilitate technical workshops with stakeholders to define enterprise application and cloud architecture requirements Partner with the architecture team to deliver end-to-end, cost-effective Generative AI solutions aligned to business goals Requirements 10 years in IT, including 5 years as a Project/Program Manager, Coordinator, Solution/Systems/Enterprise Architect, or Delivery Manager with experience Experience working as a Technical Consultant with a proven background in both pre-sales and project delivery roles Active Gemini Enterprise Deployment Certification required Hands-on ADK deployment experience, including transitioning GenAI proofs-of-concept into production-grade enterprise applications Recognized SME in ML, AI, and Generative AI, with a documented track record of accomplished projects Deep Google Cloud Platform expertise, including the networking, storage, and compute foundations required to support LLMs Client-facing consultative background - positioning GenAI services and leading C-level discussions as a trusted advisor Proven ability to lead enterprise-scale technical discussions on AI integration, data privacy, and security Experience as a Technical Consultant managing full engagement lifecycles, from solution design and MVP development to delivery