Google AI & Agentic Practice Lead

Job Title: Google AI & Agentic Practice Lead
Management Level: 07-Manager
Location: Bengaluru / India
Must-Have Skills: Google Cloud Platform, AI & Agentic Engineering, Gemini Enterprise Agent Platform, Vertex AI, Delivery Leadership, Practice Leadership, MLOps, Responsible AI.
Good-to-have skills: Google Cloud certifications, RAG, ADK, A2A, MCP, agentic governance.

Experience: 12+ years building systems and leading technical teams; 5+ years on Google Cloud in AI & Agentic Engineering.

Led distributed delivery teams with accountability for quality, execution, and outcomes.

Built reusable assets and accelerators that improved repeatability and speed across engagements.

Strong engineering fundamentals; able to review code, challenge architecture, and resolve production issues.

Hired, coached, and scaled engineers into AI and GenAI roles while linking technical depth to business value.
Educational Qualification: Bachelor-s in Computer Science, Engineering, or related field
Job Summary:
As Practice Lead, you own the AI & Agentic Engineering domain in our Google Cloud delivery organization. This practice delivers AI/ML models, intelligent agents, and generative AI solutions using Gemini Enterprise Agent Platform, Vertex AI, and ADK. You are accountable for capability, delivery, reusable assets, and technical excellence.

You report to the Head of Google Cloud Delivery and partner with onshore Technical Delivery Leads who own client relationships. They bring client context; you bring domain depth, offshore execution strategy, and delivery leadership.


Roles & Responsibilities:

Own delivery execution in the AI & Agentic Engineering domain, accountable for offshore quality, velocity, and technical outcomes across engagement in the practice area.

Partner with onshore Technical Delivery Leads who own client relationships; provide domain expertise, engineering leadership, execution capacity, and cross-border delivery discipline.

Lead technical delivery teams by staffing, coaching, and managing engineers on active engagements, ensuring work is planned, executed, and reviewed to a high standard.

Manage cross-engagement capacity, balance allocations, identify growth opportunities, address skill gaps, and optimize the resource mix.

Build reusable accelerators, templates, reference architectures, and playbooks from active projects to improve speed, consistency, and repeatability.

Partner closely with the offering development team to mature solutions from concept to productized delivery, ensuring what is sold is aligned to execution readiness.

Serve as the domain authority for AI & Agentic Engineering, own the technical backlog for the practice, support pursuits and proposals with domain expertise, advise clients where needed, and grow team capability through hiring, skill benchmarks, learning paths, and knowledge sharing.
Professional & Technical Skills:

Deep experience in Google Cloud AI and agentic technologies, including Gemini Enterprise Agent Platform, Vertex AI, Gemini models, and AI engineering delivery patterns

Strong understanding of enterprise AI/ML delivery, model lifecycle management, MLOps, evaluation frameworks, agentic AI patterns and production-grade AI systems

Hands-on knowledge of ADK, A2A, MCP, RAG, grounding, prompt engineering, and AI-augmented workflow automation

Delivery governance, team management, capacity planning, capability development, reusable assets, and distributed Agile delivery

Ability to provide credible technical guidance to internal teams and clients, with emphasis on delivery execution and domain leadership rather than solution design ownership


BONUS POINTS IF YOU HAVE:

Related Google Cloud Certifications, e.g. Google Cloud ML Engineer or Cloud Architect certification

Hands-on experience with Gemini Enterprise Agent Platform, ADK, or A2A

Production AI/ML, MLOps, responsible AI, reusable agent frameworks, or LLM evaluation tools



Qualification

TBD