Job Description: Forward Deployed Engineer (FDE)
Gemini Enterprise
Partner Resources - Gemini Enterprise (FDE Specific)
Project Brief
Project Description:
The system utilizes specialized LLM agents and Gemini Enterprise solutions to perform
automated enterprise data retrieval, multi-step logical reasoning, and knowledge
synthesis leveraging tools like NotebookLM and the Google Workspace Ecosystem. The
platform integrates robust enterprise security, Access Control Lists (ACLs), and Human-
in-the-Loop (HITL) protocols to securely connect disparate data silos (including third-
party platforms like Microsoft Entra ID/M365, Salesforce, and Atlassian) while upholding
organizational safety, security, and precision standards.
Role:
Forward Deployed Engineer (FDE) specializing in Gemini Enterprise, Agentic AI, and
Multi-Agent Systems
Responsibilities
Design, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic
workflows using Gemini Enterprise
Identify need for Pro Code Vs No Code design based on customer's problem statement
and data sources
Design Deploy and custom agents using the Agent Development Kit (ADK), and Agent
Platform AI Reasoning Engine and integrate with Gemini Enterprise
Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail,
Calendar, Meet) 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, Google
Cloud services, and 3rd-party SaaS integrations (e.g., Microsoft Entra ID / M365,
Salesforce, Atlassian) using IAM, OAuth 2.0, OIDC, and service identities.
Enforce fine-grained Access Control Lists (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 root cause analysis (RCA).




Architect Human-in-the-Loop (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 (e.g., Cloud Build, Git Hub Actions, Git Lab
CI) 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.
Establish quantitative evaluation frameworks to measure agent trajectories, tool
invocation precision/recall, and reasoning faithfulness.
Collaborate directly with client engineering and architecture teams to deploy, validate,
and operationalize enterprise agentic AI solutions in client environments.
Must-Have Skills
Core Engineering & Frameworks: Strong proficiency in Python with production-level
software engineering practices, along with deep, hands-on experience building multi-
agent systems using Google ADK (Agent Development Kit) or comparable agentic
frameworks.
Gemini & Workspace Ecosystem: Solid hands-on experience deploying and customizing
Gemini Enterprise, NotebookLM, and integrating with the broader Google Workspace
Ecosystem (APIs, Add-ons, Drive/Docs connectors).
Memory & State Architecture: Demonstrated expertise in managing agent session state,
short-term context caching, and durable long-term memory backends (vector databases,
relational/NoSQL session stores).
Third Party Tools: Experience with MCP Connectors to securely integrate core third-
party platforms (e.g., iManage, Net Documents, Relativity, Docu Sign, MS Office Suite,
Sharepoint, JIRA) with Gemini Enterprise.
Auth & Security:



Strong understanding of authentication and authorization protocols
(IAM, OAuth 2.0, OIDC, Service Accounts, Workload Identity Federation) across Google
Cloud and 3rd-party SaaS platforms (Microsoft Entra ID, Salesforce, Atlassian).
ACLs & Permissions: Deep working knowledge of enterprise Access Control Lists
(ACLs), identity federation, permission trimming, and role-based access control (RBAC)
across heterogeneous data sources.
Developer Tooling: Proficiency in developer tooling such as Agent CLI and Antigravity
for local simulation, debugging, prompt engineering, and execution graph tracing.
CI/CD & Dev Ops: Proven track record of configuring and maintaining automated CI/CD
pipelines (Cloud Build, Git Hub Actions) for agent containerization, deployment, and test
automation.

Evaluation & Debugging: Practical knowledge of AI evaluation methodologies, trajectory
analysis, and performing root cause analysis (RCA) on agent execution failures, tool
errors, and prompt regressions.
Client Collaboration: Strong technical communication, consulting acumen, and client-
facing collaboration skills within an Agile environment.
Positive-to-Have Skills
Experience with inter-agent communication protocols such as Model Context Protocol
(MCP) and Agent-to-Agent (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
(SDP/DLP) and VPC Service Controls (VPC-SC).
Qualifications and Prior Experience
4 to 6+ years of experience in software development, cloud solution architecture, and AI
engineering (preferably on Google Cloud Platform).
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
forward-deployed engineering (FDE) roles.
Familiarity with enterprise Agile development lifecycles, sprint delivery, and stakeholder
management.

📌 Partner Resources - Gemini Enterprise (FDE Specific) (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India