Lead Systems Engineer - Google Forward Deployed Engineer

EPAM Systems Inc; Pune District, Gurugram District, Coimbatore; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

EPAM Systems Inc. seeks a Lead Systems Engineer - Google Forward Deployed Engineer to design, build, and deploy production-grade agentic AI solutions for enterprise clients.

You will work hands-on with Gemini Enterprise, Google ADK, NotebookLM, and the Google Workspace ecosystem to deliver scalable, secure, and intelligent multi-agent systems. You will design, implement, and operationalize end-to-end agent architectures, secure authentication, and governance while collaborating with client

Qualifications

• 7-13 years of IT experience with 4–6+ years in software development, cloud architecture, and AI engineering, preferably on GCP.

Responsibilities

• Design, develop, and deploy production-grade multi-agent systems and agentic workflows using Gemini Enterprise.

Skills

Python

Multi-Agent Systems

GCP

Gemini Enterprise

NotebookLM

Workspace APIs

CI/CD

Agent CLI

Antigravity

IAM & Security

RBAC

Vector DBs

Tools

Agent CLI

Antigravity

MCP Connectors

Vertex AI

Google ADK

Job description

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