The next generation of technology consulting will not be driven by PowerPoint decks alone. It will be driven by leaders who can combine engineering depth, AI expertise, business understanding, and the ability to inspire customers. At EPAM, we are building an AI-Native organization and helping enterprises transform how they innovate, engineer, and operate. We are looking for a Senior GenAI Solutions Engineer who thrives in front of customers, enjoys solving complex business challenges, and wants to influence the future of AI adoption across industries. This is not a pure engineering role. This is where consulting, technology, AI, and growth converge. Responsibilities Partner with customers and account teams to understand business challenges and opportunities Translate business objectives into AI-enabled solutions and transformation roadmaps Lead discovery workshops, ideation sessions, and technical conversations with stakeholders Build credibility with executives, architects, and engineering teams Support pursuit teams and commercial organizations in strategic opportunities Design solution proposals, architectures, and implementation approaches Participate in RFPs, technical presentations, and customer demonstrations Create proof-of-concepts and prototypes that showcase business value Design solutions leveraging GenAI, Agentic AI, RAG, MCP, AI Agents, and modern AI architectures in context of AI SDLC Evaluate AI platforms, models, and orchestration frameworks Collaborate with architects, delivery teams, and business stakeholders Stay ahead of the rapidly evolving AI ecosystem Act as an AI Champion within the region Mentor engineers and technical communities Deliver workshops, internal training sessions, and enablement programs Help accelerate AI maturity across EPAM LATAM Requirements 5+ years of experience working with LLMs, Generative AI platforms, and agentic frameworks such as LangGraph, Strands, AWS Agentic Core, ADK, Anthropic, OpenAI, Gemini, and LangChain 3+ years of experience with vector databases, MCP ecosystem, and tool integrations Proficiency in cloud platforms including Azure, AWS, and GCP Skills in Python and AI frameworks for building and evaluating AI-driven solutions Background in MLOps and AI observability practices Understanding of how to evaluate LLM-based solutions, including RAG systems, agents, and multi-agentic solutions Ability to communicate complex technical concepts to both technical and non-technical audiences Showcase of executive presence, storytelling capabilities, and strong workshop facilitation skills Experience in customer-facing roles with stakeholder management responsibilities Curiosity and passion for AI innovation, with the flexibility to navigate ambiguity and move fast Collaborative mindset with a drive to shape new offerings and solutions
