Principal Forward Deployed Architect, Gemini Enterprise Platform (GCP)

Zohorecruit; Bengaluru Urban; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

AuxoAI seeks a Principal Forward Deployed Architect to lead the Gemini Enterprise Platform (GCP) program. You own the end-to-end architecture across the GenAI foundation, GEAP agent landscape, the grounding graph, and enterprise adoption, coordinating cross-functional teams and client reviews to deliver a scalable AI ecosystem on Google Cloud.

You will drive design coherence, governance and risk management, engage in significant pre-sales work, and mentor senior engineers across onshore and

Qualifications

• Postgraduate degree or equivalent practical experience in computer science/engineering.
• 12+ years in engineering, architecture or technical delivery leadership including ownership of production systems.
• Expert depth in two or more layers of GenAI platform stack, context-graph/semantic modelling, data platform, and runtime/governance.
• Delivered production GenAI or agent systems on GCP or comparable cloud with enterprise grounding.

Responsibilities

• Own target architecture across four layers: GenAI platform foundation, GEAP landscape, context-graph/data foundation, and enterprise adoption.
• Define reference patterns for agent construction and runtime isolation and governance.
• Design grounding/knowledge graphs and RAG strategies connecting to agents; ensure data residency considerations are resolved.
• Arbitrate cross-track trade-offs when multiple engineers are deployed to the same client and document rationale.
• Represent AuxoAI in client security, compliance and architecture review boards; address model-governance and data-governance.

Skills

Senior leadership

Architectural decisioning

Client liaison

Presales involvement

Risk assessment

Education

Master's degree in Computer Science or Engineering

Tools

Vertex AI

BigQuery

Spanner Graph

GKE

Job description

Principal Forward Deployed Architect, Gemini Enterprise Platform (GCP)

Bangalore South, India | Posted on 09/23/2026

You are theperson a client trusts to turn an ambitious Gemini Enterprise vision into abusiness outcome that lasts. As Principal Forward Deployed Architect on anaccount, you own the result -- the value the client set out to create — andwith it the technical whole that produces that value: the GenAI platformfoundation on Google Cloud, the agent landscape built on the Gemini EnterpriseAgent Platform (GEAP), the context-graph and data foundation those agentsreason over, and the enterprise rollout into the Gemini Enterprise app.

Wherespecialist engineers each own an individual agent, MCP server or data pipeline,you own the whole — deep in the agent platform and the context / datafoundation, fluent enough across governance, runtime and adoption to design,sequence and defend the program end to end. You are the senior technicalcounterpart the client's executives call before they have decided what tobuild; more importantly, you are the reason they keep calling. You make GoogleCloud's AI foundation deliver the outcomes.

This roleexists because standing up a production agent ecosystem on GEAP is not asingle-layer problem — model choice, agents, grounding graph, governanceperimeter and change management are load-bearing on one another — and becauseour largest clients will accept only one senior technical owner rather thanseveral.

DeploymentModel

Placed atone large Gemini Enterprise account, or holding technical ownership across twoor three smaller concurrent engagements. You may direct AuxoAI delivery teams,including offshore and onshore Forward Deployed Engineers and client engineers,on the same program — you own the design coherence across it. Significantpre-sales involvement is expected: the GEAP target architecture, the GCPlanding-zone approach, effort estimates, and the technical case in proposalsfor the practice's largest Gemini opportunities.

KeyResponsibilities

Whole-programarchitecture

• Own the target architectureacross four layers — GCP GenAI platform foundation, the GEAP agentlandscape, the context-graph / data foundation, and enterprise adoption —and sequence delivery across all four.
  
• Set the reference patterns forhow agents are built (ground-up in ADK vs. forked and hardened from AgentGarden templates), where they run (Agent Engine managed vs. Cloud Run vs.self-managed GKE), how they are isolated (sandbox strategy), and how theyare governed.
  
• Design the context-graphfoundation — BigQuery, BigQuery graph (GQL) and/or Spanner Graph — and thegrounding / RAG strategy that connects it to agents, including entityresolution, semantic modelling and retrieval over Vertex AI Vector Search.
  
• Identify decisions in one layerthat are load-bearing for others (e.g., a grounding-data residency choicethat constrains the runtime target and the governance perimeter) and forcethem to resolution before delivery commits, not during it.
  
• Arbitrate cross-tracktrade-offs where multiple Forward Deployed Engineers are deployed to thesame client, with a written rationale.
  
• Maintain technical proximity:review agent designs and evaluation results, interrogate trajectory andlatency behaviour, participate in incident reviews, and perform selectivehands-on work where it materially changes the outcome.
  
• Represent AuxoAI in theclient's security, compliance and architecture review boards, includingthe model-governance and data-governance forums.
  

Clientand commercial

• Advise client executives ontrade-offs, sequencing, delivery risk and what not to build — includingwhich use cases are not yet safe to automate.
  
• Own the technical scope,estimate and defence of proposals and statements of work for the accountand for major Gemini Enterprise prospects.
  
• Give AuxoAI leadership anaccurate read on delivery risk, including remediation plans andconsumption-cost exposure (runtime vCPU-hours, Sessions and Memory events,model tokens, sandbox compute).
  

Enablementand practice contribution

• Enable the client's ownplatform, data and security leadership to operate and extend the agentlandscape and context graph, with named client owners for each majorcomponent.
  
• Develop the Forward DeployedEngineers working alongside you on the account, whether or not they reportto you.
  
• Contribute GEAP referencearchitectures, context-graph patterns, estimation models and governanceblueprints that raise the practice standard.
  

OutcomeOwnership

You areaccountable for the outcome, not the artifact. Long after AuxoAI rolls off, theclient's agent ecosystem has to keep earning its place — grounded, governed,evaluated and adopted, still delivering the business result it was built for.When an agent delivered under your architecture regresses, leaks data, breachesa policy or loses the users it was meant to serve, you own the explanation tothe client and the plan to make it right.

Expertdepth in at least two of the areas below; working competence in all.

Area

Technologies

ADK (agent types, orchestration, tools), AgentGarden (ground-up and template-based builds), Model Garden, Agent Studio,Agents CLI, Agent Engine runtime (managed / Cloud Run / GKE), Sessions &Memory Bank, MCP and A2A

BigQuery, BigQuery graph (GQL), Spanner Graph,knowledge-graph and entity-resolution design, semantic layers, Vertex AIVector Search, RAG / grounding architecture

BigQuery, Dataform, Dataproc (Spark), Pub/Sub,Dataplex Universal Catalog / Knowledge Catalog (lineage, classification, dataquality), Sensitive Data Protection (DLP)

Agent governance & security

Agent Gateway, Model Armor, Semantic Governance(Natural Language Constraints), Agent Identity & Registry, ContentProtection, Security Command Center

Enterprise adoption

Gemini Enterprise app, agent catalog / Agent Gallerypublishing, Google Workspace integration, change management and adoption

MinimumQualifications

• Master's degree in ComputerScience, Engineering, Information Systems or a related field, orequivalent practical experience.
  
• 12+ years in engineering,architecture or technical delivery leadership, including senior technicalownership of production systems.
  
• Expert depth in at least twoof: the agent / GenAI platform layer, the context-graph andsemantic-modelling layer, the cloud data-platform layer, and the cloudruntime / governance layer — with working competence across the rest,demonstrable through an architecture walkthrough.
  
• Delivered at least oneproduction GenAI or agent system on GCP (Vertex AI / Agent Platform) or adirectly comparable cloud, including grounding over an enterprise data orknowledge foundation.
  
• End-to-end ownership oftechnical design for at least two client engagements or major cross-teamprograms, from discovery through production.
  
• Experience as the single seniortechnical counterpart to a client's executive team on an engagement ofmaterial size.
  
• Hands-on depth in BigQuery andat least one graph or semantic store (Spanner Graph, BigQuery graph, Neo4jor equivalent).
  
• Delivery inside at least oneregulated environment, with the ability to describe a design decision theregulation forced.
  
• Experience owning the technicalscope, estimate and defence of a proposal or statement of work.
  

PreferredQualifications

• Hands-on with the GeminiEnterprise Agent Platform specifically — ADK, Agent Garden, Model Garden,Agent Engine — or a rapid, demonstrable path to it from adjacent agentframeworks (LangGraph, CrewAI, Amazon Bedrock Agents, Azure AI Foundry).
  
• Experience designing andoperating MCP servers (off-the-shelf, third-party and custom) andmulti-agent (A2A) topologies.
  
• Experience building a knowledge/ context graph for retrieval grounding at enterprise scale.
  
• Consulting, systems-integratoror professional-services background at principal or equivalent level.
  
• A record of developing seniorengineers or architects, and of leading hybrid onshore / offshore teams atscale.
  
• Experience deciding against atechnically attractive approach for commercial, cost or governancereasons, and defending that to both client and internal stakeholders.