Generative AI Senior Developer – Google Cloud (Contract to Hire) - Hybrid Remote – Western States Residents ONLY

Entisys Solutions Inc • Irvine, CA

25d • $80 - $90 • Hybrid

About The Position

The Advanced Generative AI Developer is a hands-on consultant responsible for designing, building, and deploying production-ready Generative AI and agentic solutions on Google Cloud. This role requires strong Python and cloud development experience, practical knowledge of Google Agent Development Kit, Gemini, Vertex AI, and GCP-native application and data services. The consultant will work directly with client and project teams to translate business requirements into secure, scalable, and maintainable AI solutions.

Requirements

• 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, including agents, tools, workflows, sessions, state, and multi-agent patterns.
• 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.
• Candidates are not expected to have experience with every listed GCP service. However, they must have hands-on experience delivering Generative AI solutions and be able to explain their architecture and implementation decisions.

Nice To Haves

• Experience delivering client-facing Google Cloud consulting projects.
• Experience leading a technical workstream from discovery through production deployment.
• Experience deploying ADK agents using Agent Engine, Cloud Run, or GKE.
• Experience implementing MCP servers, custom agent tools, or enterprise integrations.
• Experience with Vertex AI Vector Search, BigQuery Vector Search, Document AI, Apigee, Pub/Sub, Eventarc, or Workflows.
• Experience with Terraform, Cloud Build, Artifact Registry, and automated GCP deployment pipelines.
• Experience implementing AI evaluation, agent testing, observability, guardrails, and cost monitoring.
• Relevant Google Cloud certifications.

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.

Benefits

• Internal, and subsidize external, trainings
• Reimburse the cost of technology certification exams and / or renewals
• Work life fit as a core value
• Numerous opportunities to interface with senior leadership
• Benefit from mentorship internally or through introductions through external networks

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed