Senior Generative AI Developer – Google Cloud

• 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 Big Query, 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 work streams and provide design reviews, code reviews, and guidance to other developers.
• Participate in client discovery, architecture, testing, deployment, and knowledge-transfer activities.

• 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 Big Query 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.

Demonstrates expertise in developing and deploying Generative AI applications on Google Cloud, utilizing advanced Python programming and integrating various Google Cloud services. Proficient in building APIs, data pipelines, and implementing security measures while ensuring high-quality, scalable, and reliable solutions.

• Google Cloud Application Development
• Advanced Python Development
• Generative AI Application Building
• API Development with FastAPI
• Data Pipeline Construction

• Python
• Google Cloud
• Generative AI
• API Development
• Big Query
• SQL
• Microservices
• CI/CD
• Docker
• Event-Driven Architecture

• Generative AI
• Agentic Applications
• MCP
• Asynchronous Processing
• Retrieval-Augmented Generation
• Data Services
• Cloud Security
• Monitoring
• Logging
• Orchestration Patterns

• Google Agent Development Kit
• Agent Engine
• Cloud Run
• GKE
• Vertex AI
• Cloud Functions
• Document AI
• Secret Manager
• Git
• Infrastructure as Code