Project Role : Custom Software Engineer
Project Role Description : Design, build and configure applications to meet business process and application requirements.
Must have skills : Google Cloud Machine Learning Services
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
We are looking for a seasoned Manager – GenAI & Agentic Architecture with deep expertise in designing and delivering enterprise-grade Agentic AI solutions using Google Agent Development Kit (ADK), Vertex AI, and Gemini Enterprise.
This role demands a strong technical leader who can bridge business requirements, enterprise data platforms, and agent-based AI systems. As a Manager, you will drive architectural decisions, guide delivery teams, and ensure scalable, secure, and high-quality implementation of multi-agent and agent-of-agents platforms.
Roles & Responsibilities
Own the overall enterprise architecture and strategy for GenAI and Agentic AI platforms across industries and clients
Define reference architectures, target-state designs, and governance models for multi-agent and agent-of-agents systems, A2A (Agent-to-Agent) communication frameworks, and MCP-based agent orchestration platforms
Act as a strategic advisor to executive stakeholders on how to transform enterprise operations using agentic AI architectures
Lead large transformation programs embedding autonomous and semi-autonomous agents into core business workflows
Oversee Gemini Enterprise adoption, grounding models using 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 platforms, external systems, and partner data
Provide architectural oversight for advanced RAG and Graph RAG solutions, including enterprise-wide chunking and retrieval standards and knowledge graph–driven reasoning and decision intelligence
Establish enterprise standards for prompt engineering and agent orchestration, including planner–executor and reflection patterns
Define and govern agent observability frameworks at scale, including agent execution visibility, tool-call tracing and auditing, and performance, cost, and outcome monitoring
Define agent security and trust architectures, including policy-driven agent behavior, secure tool and data access, and guardrails for autonomous actions
Drive identity-aware GenAI architectures, with strong governance over Workload Identity Federation, federated credentials, and secure enterprise and partner integrations
Enable and mentor senior architects, managers, and technical leaders across the organization
Govern delivery excellence, scalability, compliance, and platform resilience
Must Have Skills
Strong leadership in Google Agent Development Kit (ADK)–based architectures
Deep understanding of agentic systems, multi-agent design, and A2A patterns
Expertise in MCP or equivalent agent control-plane architectures
Proven experience with Vertex AI Machine Learning services at enterprise scale
Hands-on and strategic experience with Gemini Enterprise
Strong command over RAG, Graph RAG, and knowledge-driven AI systems
Experience establishing agent observability, monitoring, and governance
Expertise in agent security, trust, and safety architectures.
Strong understanding of Workload Identity Federation and federated credentials
Executive-level capability in defining GenAI strategy aligned to business outcomes
Good to Have Skills
Google Cloud Machine Learning Services certifications
Experience with enterprise data and integration platforms
Thought leadership in AI governance and responsible AI frameworks
Additional Information
15+ years of relevant experience, with significant leadership experience in AI / GenAI platforms
Proven track record of leading large-scale enterprise AI transformations
Strong educational background in computer science, engineering, or related fields
Exceptional communication, executive presence, and stakeholder management skills
