Project Role : Program/Project Management Lead Project Role Description : Lead business and technology outcomes for assigned program, project, or contracted service. Leverage standard tools, methodologies and processes to deliver, monitor, and control service level agreements.

Must have skills : Google Cloud Machine Learning Services Good to have skills : GCP Dataflow Minimum 15 Year(s) Of Experience Is Required Educational Qualification : BTech Summary We are seeking a Senior Manager – GenAI & Agentic Architecture with deep expertise in Google Agent Development Kit (ADK), Agent-to-Agent (A2A) and MCP-based orchestration, and Vertex AI Machine Learning services. This role is responsible for designing, scaling, and governing enterprise-grade multi-agent systems that leverage Generative AI, RAG, Graph RAG, and Google foundation models. The ideal candidate is a visionary architect who can bridge business workflows, data platforms, and autonomous AI agents at scale.

Roles &

Responsibilities Own end-to-end agentic architecture for enterprise GenAI platforms using Google ADK and Vertex AI Define multi-agent and agent-of-agents architectures leveraging A2A (Agent-to-Agent) communication patterns Design and operationalize MCP-based orchestration layers for agent lifecycle management, coordination, and governance Establish reference architectures, design patterns, and reusable frameworks for scalable agent platforms Architect advanced RAG pipelines, including optimal chunking strategies, embedding selection, retrieval tuning, and re-ranking Design and implement Graph RAG solutions using knowledge graphs for relationship-aware reasoning and contextual enrichment Lead Gemini Enterprise implementations, grounding GenAI models on first-party (1P) enterprise data stores such as BigQuery, GCS, and internal knowledge bases, as well as third-party (3P)



data sources such as SaaS systems and external content repositories Define and implement agent observability and monitoring frameworks, including agent execution tracing, tool-call visibility, prompt and response auditing, and latency, cost, and quality metrics Own agent security architecture, covering secure tool access and permissions, policy-based agent behavior, and guardrails for autonomous actions Drive identity-aware GenAI architecture, with solid understanding of Workload Identity Federation, federated credentials, and secure access to enterprise systems, APIs, and data stores Govern adoption of Vertex AI Machine Learning services, including embeddings, model evaluation, pipelines, and inference Standardize prompt engineering and orchestration techniques, including role prompting, planner–executor patterns, and self-reflection loops Act as a strategic advisor to senior stakeholders on embedding agentic AI into enterprise processes Mentor architects and senior engineers oversee delivery governance, scalability, and platform reliability Qualified & Technical Skills Must Have Skills Google Agent Development Kit (ADK) – hands-on enterprise usage Agent-to-Agent (A2A) communication architectures MCP (Model / Multi-Agent Control Plane) or equivalent agent orchestration patterns Vertex AI Machine Learning services (training, prediction, embeddings, pipelines, evaluation) Gemini models and GenAI APIs on Google Cloud Deep expertise in RAG, chunking strategies, retrieval optimization Graph RAG / Knowledge Graph–based reasoning architectures Advanced prompt engineering, prompt chaining, and orchestration Experience building autonomous and semi-autonomous agents with tool calling Good to Have Google Cloud certifications (Professional Google Machine Learning services / Cloud AI Engineer) BigQuery, GCS, Pub/Sub integration Enterprise data governance and AI safety frameworks Additional Information: 15–18+ years overall, with 5+ years in AI / GenAI

📌 Program/Project Management Lead (Bengaluru)
🏢 Accenture in India
📍 Bengaluru