Lead Systems Engineer - Google Forward Deployed Engineer

Office in India: Gurugram,

Google Cloud Platform

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We are seeking a Lead Systems Engineer - Google Forward Deployed Engineer to design, build, and deploy production-grade agentic AI solutions for enterprise clients, working hands-on with Gemini Enterprise, Google ADK, and the broader Google Workspace ecosystem to deliver scalable, secure, and intelligent multi-agent systems.

Responsibilities

Design, develop, and deploy production-grade Multi-Agent Systems and agentic workflows using Gemini Enterprise
Identify the need for Pro Code vs No Code design based on customer's problem statement and data sources
Build and deploy custom agents using the ADK and Agent Platform AI Reasoning Engine, and integrate them with Gemini Enterprise
Build native integrations across the Google Workspace Ecosystem and NotebookLM for grounded enterprise research, document automation, and conversational discovery
Architect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions
Implement end-to-end authentication and authorization perimeters for agents, GCP services, and 3rd-party SaaS integrations using IAM, OAuth 2.0, OIDC, and service identities
Enforce fine-grained ACLs, user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries
Utilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and RCA
Architect HITL workflows, ensuring seamless Interrupt and Resume patterns between autonomous agents and human experts for critical decision points
Build and maintain automated CI/CD pipelines to manage versioned agent deployments, automated testing, and continuous regression evaluations
Implement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability
Collaborate directly with client engineering and architecture teams to deploy, validate, and operationalize enterprise agentic AI solutions in client environments

Requirements

7-13 years of overall IT experience, including 4 to 6+ years in software development, cloud solution architecture, and AI engineering, preferably on GCP
Proficiency in Python with production-level software engineering practices, and expertise in building multi-agent systems using Google ADK or comparable agentic frameworks
Hands-on experience deploying and customizing Gemini Enterprise, NotebookLM, and integrating with the Google Workspace Ecosystem, including APIs, Add-ons, and Drive/Docs connectors
Expertise in managing agent session state, short-term context caching, and durable long-term memory backends such as vector databases and relational/NoSQL session stores
Experience with MCP Connectors to securely integrate core third-party platforms with Gemini Enterprise
Understanding of authentication and authorization protocols across GCP and 3rd-party SaaS platforms, including IAM, OAuth 2.0, and OIDC
Knowledge of enterprise ACLs, identity federation, permission trimming, and RBAC across heterogeneous data sources
Proficiency in developer tooling such as Agent CLI and Antigravity for local simulation, debugging, prompt engineering, and execution graph tracing
Proven track record of configuring and maintaining automated CI/CD pipelines for agent containerization, deployment, and test automation
Knowledge of AI evaluation methodologies, trajectory analysis, and performing RCA on agent execution failures, tool errors, and prompt regressions
Proven track record of designing, building, and deploying production AI agents or enterprise GenAI solutions using ADK, Vertex AI, or Gemini
Hands-on experience in customer-facing technical delivery, solutions engineering, or FDE roles, with familiarity with enterprise Agile SDLC, sprint delivery, and stakeholder management

Nice to have

Experience with inter-agent communication protocols such as MCP and A2A architectures
Experience integrating agents with Enterprise Knowledge Graphs, structured ontologies, and hybrid vector search systems
Experience with enterprise data security frameworks such as Sensitive Data Protection and VPC Service Controls