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

About the role

e360 is a 30+ year privately-owned company focused on its people, clients, and leading technologies. Our Cloud Services Division helps clients manage their Cloud technology. Our team includes leaders who deliver innovative consulting solutions leveraging leading and emerging technologies. We offer professional development and growth opportunities tailored to individual goals.

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 like BigQuery, Vertex AI Vector Search, Cloud Storage, and Document AI.
• Develop APIs, microservices, agent tools, MCP integrations, and event-driven workflows.
• Implement 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.
• Implement 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.

Qualifications

• Candidates are not expected to have experience with every listed GCP service but must have hands-on experience delivering Generative AI solutions and be able to explain their architecture and implementation decisions.

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.