Senior Forward Deployed Engineer, Gemini Enterprise Platform
AuxoAI Engineering Pvt. Ltd. · CA, US
11 days agoImpress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Senior Forward Deployed Engineer, Gemini Enterprise Platform role.
Rezi rewrites your resume against AuxoAI Engineering Pvt. Ltd.'s job description. Free.
Tailor your resume to this Senior Forward Deployed Engineer, Gemini Enterprise Platform role.
Rezi rewrites your resume against AuxoAI Engineering Pvt. Ltd.'s job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Senior Forward Deployed Engineer, Gemini Enterprise Platform posting at AuxoAI Engineering Pvt. Ltd. — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Senior Forward Deployed Engineer, Gemini Enterprise Platform posting at AuxoAI Engineering Pvt. Ltd. — free, in seconds.
About the Role
As a Senior Forward Deployed Engineer, you will transform client use cases from concept to production-ready agents on the Gemini Enterprise Agent Platform. You will build agents, integrate tools, and manage context graphs, focusing on delivering measurable value and ensuring client adoption and ownership. This role requires deep technical expertise and the ability to operate credibly within a client's environment.
Responsibilities
- Build agents ground-up in ADK and by forking and hardening Agent Garden templates, defining instructions, model selection, tools, orchestration, grounding, and memory.
- Select and bind models for cost and latency; implement structured output, thinking-level, and safety configuration.
- Run evaluation and simulation before ship, including trajectory and response metrics, and synthetic-user simulation.
- Build MCP servers to expose client systems and data as agent tools.
- Integrate off-the-shelf and third-party MCP servers.
- Wire OpenAPI and Google Cloud toolsets.
- Implement multi-agent (A2A) hand-offs.
- Build the context-graph foundation on BigQuery graph (GQL) and/or Spanner Graph.
- Build the retrieval/grounding path (Vertex AI, Vector Search, Embeddings, RAG) that connects to agents.
- Build and operate the supporting data stack: BigQuery models, Dataform pipelines, Dataproc jobs, and Pub/Sub streams.
- Implement cataloguing, lineage, and classification in Dataplex Universal Catalog / Knowledge Catalog.
- Deploy agents to Agent Engine, Cloud Run, or GKE via the Agents CLI and infrastructure-as-code.
- Instrument observability (Cloud Trace / OpenTelemetry).
- Apply governance (Model Armor, Semantic Governance, Agent Identity).
- Publish agents into the client's Gemini Enterprise app catalog.
- Configure Google Workspace integration.
- Provide pre-sales support, including proofs of concept, demos, and effort inputs.
- Pair with client engineers and ensure they can maintain and extend built solutions.
Requirements
- Master's or Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
- 6+ years building and shipping production software or data / ML systems, with strong Python.
- Hands-on experience building LLM agents with a code-first framework (ADK preferred; LangGraph, CrewAI, LlamaIndex or Amazon Bedrock Agents accepted) — including tools, retrieval grounding and evaluation.
- Strong BigQuery and SQL, and hands-on experience with at least one graph store (Spanner Graph, BigQuery graph, Neo4j or equivalent).
- Built at least one data pipeline in production (Dataform, Dataproc / Spark, dbt or equivalent) and worked with a streaming / eventing system (Pub/Sub or equivalent).
- Deployed services to a managed or container runtime (Cloud Run, GKE, Kubernetes or equivalent) with infrastructure-as-code (Terraform).
- Client-facing or embedded delivery experience — able to pair with a client's engineers and hand over cleanly.
Skills
- Python
- LLM agents
- ADK
- LangGraph
- CrewAI
- LlamaIndex
- Amazon Bedrock Agents
- Tools integration
- Retrieval grounding
- Evaluation
- BigQuery
- SQL
- Spanner Graph
- BigQuery graph
- Neo4j
- Dataform
- Dataproc
- Spark
- dbt
- Pub/Sub
- Cloud Run
- GKE
- Kubernetes
- Terraform
- Gemini Enterprise Agent Platform
- ADK
- Agent Garden
- Model Garden
- Agent Engine
- Agent Studio
- Agents CLI
- MCP servers
- OpenAPI
- Google Cloud toolsets
- Vertex AI
- Vector Search
- Embeddings
- RAG
- Dataplex Universal Catalog
- Knowledge Catalog
- Cloud Trace
- OpenTelemetry
- Model Armor
- Semantic Governance
- Agent Identity
- Google Workspace integration
- autoraters
- trajectory metrics
- Google Cloud Professional certification (Data Engineer, Machine Learning Engineer, or Cloud Developer)
Location
- Embedded in a client engagement
Work Type
- Embedded
- Full-time
Experience Level
- Senior
Education Level
- Master's or Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
About the Company
- The Gemini Enterprise Agent Platform is used to build and deploy agents.