Generative AI Senior Developer - Google Cloud (Contract to Hire) - Hybrid Remote - Western States Residents ONLY
Role details
Job location
Tech stack
Job description
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.
What You'll Do
- 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.
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., * 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.
Professional Skills
- Strong consulting, communication, and problem-solving skills.
- Ability to translate business requirements into practical technical solutions.
- Ability to explain complex AI and cloud concepts to technical and non-technical stakeholders.
- Strong documentation and technical leadership skills.
- Ability to work independently and manage changing project priorities.
- Ability to identify and communicate technical risks, dependencies, and blockers.
- Willingness to mentor other developers and contribute to reusable delivery standards.
Critical Success Factors
- Ability to independently design and deliver production-ready AI solutions on Google Cloud.
- Strong practical knowledge of Google ADK, Gemini, Vertex AI, and GCP architecture.
- Ability to build agents that securely interact with APIs, data, tools, and enterprise systems.
- Ability to determine when to use agentic, deterministic, serverless, containerized, or managed-service patterns.
- Commitment to security, testing, observability, governance, maintainability, and cost control.
- Ability to own technical workstreams and consistently deliver high-quality client outcomes.
Benefits & conditions
$80 - $90 an hour - Temp-to-hire