We are seeking a Senior Delivery Manager to lead end-to-end delivery of data and AI programs, guiding distributed teams through platform modernization, GenAI initiatives, and production-grade analytics solutions while acting as a trusted advisor to client leadership. Req# 1100434489 Responsibilities Own scope, schedule, quality, budget, and margin for data engagements, from discovery and estimation through production and hypercare Lead delivery of data platform modernization (lakehouse, cloud migration, streaming, data mesh / data products) and the AI use cases built on it: RAG and agentic applications, ML models, analytics Make sure data is AI-ready by driving data quality, lineage, metadata, access controls, and governance as delivery requirements rather than afterthoughts Bring AI-accelerated practices into your teams: AI coding assistants, agent-assisted pipeline and test generation, automated documentation, and AI-driven planning, risk, and status reporting Set up human-in-the-loop controls, auditability, and responsible-AI practices appropriate to the client's regulatory context Measure and report the impact: delivery velocity, quality, cost-to-serve, and AI adoption on the engagement Lead distributed, cross-functional teams of 15-60+ people (data engineers, architects, analysts, data scientists, ML/AI engineers, QA) across nearshore and offshore locations Act as the primary delivery contact for client Directors and VPs: run governance and steering meetings, manage escalations, and build trusted-advisor relationships Work with solution architects on technical decisions and hold teams to EPAM's engineering-excellence standards Support pre-sales by shaping solutions, estimates, SOWs, and delivery approaches for data and AI opportunities Find expansion opportunities within your accounts and help move engagements toward outcome-based or managed-service commercial models Capture reusable accelerators and delivery patterns and contribute them back to the practice Mentor delivery leads and engineers, and grow AI-native delivery capability across the practice Requirements 8+ years in IT, with 4+ years in delivery management of data or analytics programs with distributed teams 3+ years of prior hands-on experience as a Data Engineer, Data Architect, BI/Analytics Engineer, or Data Scientist A track record of delivering data platforms to production on at least one major cloud (AWS, Azure, or GCP) and a modern data platform (Databricks, Snowflake, Microsoft Fabric, BigQuery, or similar) Delivery experience on at least one AI/ML or GenAI initiative in production (for example RAG, agentic workflows, forecasting, recommendations, document intelligence) Hands-on, everyday use of AI tools in your own delivery practice, with examples you can show Solid understanding of data governance, data quality, and MLOps/LLMOps fundamentals Full ownership of project financials: budget, forecasting, margin, and change control Strong client-facing, risk management, and executive communication skills at Director/VP level Nice to have Experience in pre-sales, RFP responses, or solution shaping Fixed-price, managed-service, or outcome-based delivery experience Industry depth in financial services, healthcare/life sciences, retail/CPG, manufacturing, or automotive Cloud, Databricks/Snowflake, or frontier AI lab certification (e.g. Anthropic, OpenAI, Gemini or similar); PMP, SAFe, or similar Experience in a consulting or professional-services environment
