Google AI & Agentic Practice Lead

Accenture; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture in Bengaluru, India seeks a Google AI & Agentic Practice Lead to own the AI & Agentic Engineering domain within our Google Cloud delivery organization. You drive capability, delivery excellence, reusable assets and technical leadership across engagements.

You report to the Head of Google Cloud Delivery and partner with client-facing leads to align delivery strategy with business outcomes, coaching offshore teams and guiding architecture reviews.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 12+ years building systems and leading technical teams.
• 5+ years on Google Cloud in AI & Agentic Engineering.

Responsibilities

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

Skills

Google Cloud Platform

AI & Agentic Engineering

Gemini Enterprise Agent Platform

Vertex AI

Delivery Leadership

Practice Leadership

MLOps

Responsible AI

Education

Bachelor's in Computer Science

Job description

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