Senior GenAI Engineer: Google Cloud & Agent Architect

Jobtailor

Phoenix (AZ)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Jobtailor is seeking a seasoned specialist to design and deploy Generative AI applications and intelligent agents on Google Cloud in Phoenix. You will craft single- and multi-agent solutions with the Google Agent Development Kit, integrating Gemini models with enterprise APIs and data stores to support business workflows.

You will deploy on Cloud Run, GKE, or related services, architect RAG pipelines, and build scalable APIs with FastAPI.

Qualifications

  • Significant experience developing and deploying applications on Google Cloud.
  • Advanced Python development experience.
  • Hands-on experience building Generative AI or agentic applications.
  • Experience with Google Agent Development Kit.
  • Experience integrating Gemini models using Vertex AI or Google Gen AI SDKs.
  • Experience with Agent Engine, Cloud Run, GKE, Cloud Functions, or similar GCP runtimes.
  • Experience designing and implementing RAG solutions.
  • Experience with BigQuery and Google Cloud data services.
  • Experience building APIs using frameworks such as FastAPI.
  • Experience with REST APIs, asynchronous processing, event-driven architecture, and microservices.
  • Understanding of MCP and its use in connecting agents to enterprise tools and systems.
  • Experience with SQL, document stores, object storage, embeddings, semantic search, or vector databases.
  • Experience with Git, automated testing, CI/CD, Docker, and infrastructure as code.
  • Understanding of Google Cloud IAM, service accounts, Secret Manager, networking, logging, and monitoring.
  • Ability to evaluate tradeoffs involving model quality, latency, security, scalability, reliability, and cost.

Responsibilities

  • Design, build, test, and deploy Generative AI applications and intelligent agents on Google Cloud.
  • Develop single-agent and multi-agent solutions using Google Agent Development Kit.
  • Integrate Gemini models with enterprise APIs, databases, applications, and business workflows.
  • Deploy AI applications using Agent Engine, Cloud Run, GKE, or other appropriate GCP services.
  • Build Retrieval-Augmented Generation solutions using services such as BigQuery, Vertex AI Vector Search, Cloud Storage, and Document AI.
  • Develop APIs, microservices, agent tools, MCP integrations, and event-driven workflows.
  • Build data pipelines to ingest, transform, chunk, embed, index, and retrieve structured and unstructured data.
  • Implement session management, memory, tool calling, human approval, and agent orchestration patterns.
  • Apply automated testing, CI/CD, logging, monitoring, tracing, evaluation, and cost-management practices.
  • Implement Google Cloud security using IAM, service accounts, Workload Identity Federation, Secret Manager, and private networking.
  • Troubleshoot issues across agents, models, APIs, data pipelines, integrations, security, and cloud deployments.
  • Create architecture diagrams, technical designs, API specifications, deployment guides, and operational documentation.
  • Own technical workstreams and provide design reviews, code reviews, and guidance to other developers.
  • Participate in client discovery, architecture, testing, deployment, and knowledge-transfer activities.

Skills

Python
Generative AI
Google Cloud
Agent development
Vertex AI
APIs
FastAPI
CI/CD
BigQuery
GKE/Cloud Run
Security
Data pipelines
Embeddings/Vector DB

Tools

Google Agent Development Kit
Gemini models integration
Cloud Run
Vertex AI SDKs
Docker
Kubernetes

Job description

Jobtailor is seeking a seasoned specialist to design and deploy Generative AI applications and intelligent agents on Google Cloud in Phoenix. You will craft single- and multi-agent solutions with the Google Agent Development Kit, integrating Gemini models with enterprise APIs and data stores to support business workflows.

You will deploy on Cloud Run, GKE, or related services, architect RAG pipelines, and build scalable APIs with FastAPI.

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