Role : Senior Developer/ Leads
Location : San Leandro CA (Onsite)
Hire Type (FTE/Contract): Contract
Must have :
Senior Developer/ Leads with Java Python Google ADK comfortable working with LLMs MCP building Agents generating code
Role Summary
Design and build secure scalable backend services in Java (Spring Boot) and Python and deliver production-grade AI agent capabilities using Google Agent Development Kit (ADK).
Build agentic workflows that can use tools maintain session context/memory and generate/refactor code with strong human-in-the-loop review and governance.
Integrate agents with enterprise systems and data sources via Model Context Protocol (MCP) and standard APIs with strong attention to security observability reliability and cost controls.
Key Responsibilities
Develop high-scale microservices and APIs using Java 17 Spring Boot and REST/gRPC; apply solid engineering fundamentals (OOP concurrency performance).
Build Python services (e.g. FastAPI) that host agent logic and AI integrations; implement robust error handling retries and structured outputs.
Create and orchestrate agents using Google ADK: define agents attach tools/functions manage sessions and memory and implement multi-step workflows (sequential/parallel/routed).
Implement MCP-based integrations: expose internal tools/resources as MCP servers (where applicable) and consume MCP tools from agents/clients securely.
Deliver LLM features (tool/function calling prompt & context engineering evaluation) and implement RAG patterns with embeddings and vector databases when grounding is required.
Containerize and deploy services using Docker and Kubernetes (AKS/OCP preferred); build CI/CD pipelines (GitHub Actions/Jenkins/Harness) with quality gates.
Implement observability (logs/metrics/tracing) SLOs/SLIs and performance testing; participate in incident response and root cause remediation.
Mentor engineers perform design/code reviews and collaborate with product security data and platform teams in an Agile/Scrum environment.
Must-Have Skills
Strong Java backend engineering (Java 17 Spring Boot microservices REST/gRPC).
Strong Python engineering (OOP typing async patterns packaging) and service development.
Hands-on experience building agents and workflows with Google ADK (agents tools sessions/memory).
Comfort working with LLMs: tool/function calling structured outputs prompt & context engineering safety considerations.
Understanding of MCP concepts (resources tools prompts; client-server model) and ability to integrate tools using MCP or standard APIs.
Ability to produce high-quality code with AI-assisted code generation plus strong review/verification and testing discipline.
Security fundamentals: OAuth2/OIDC JWT secure coding secrets management; familiarity with mTLS/cert management is a plus.
Cloud-native fundamentals: Docker Kubernetes; CI/CD pipelines; basic monitoring/observability.
Good-to-Have Skills
LangChain/LangGraph or similar orchestration frameworks; experience combining them with ADK where useful.
Vector DB experience and RAG evaluation practices.
GCP/Vertex AI (or other cloud LLM hosting) and production deployment patterns (Cloud Run/Agent Engine).
Kafka/Flink or event-driven architectures for real-time systems.
Front-end exposure (React/Angular) for agent-driven UIs or developer tooling.
Role : Senior Developer/ Leads Location : San Leandro CA (Onsite) Hire Type (FTE/Contract): Contract Must have : Senior Developer/ Leads with Java Python Google ADK comfortable working with LLMs MCP building Agents generating code Role Summary Design and build secure scalable backen...
Role : Senior Developer/ Leads
Location : San Leandro CA (Onsite)
Hire Type (FTE/Contract): Contract
Must have :
Senior Developer/ Leads with Java Python Google ADK comfortable working with LLMs MCP building Agents generating code
Role Summary
Design and build secure scalable backend services in Java (Spring Boot) and Python and deliver production-grade AI agent capabilities using Google Agent Development Kit (ADK).
Build agentic workflows that can use tools maintain session context/memory and generate/refactor code with strong human-in-the-loop review and governance.
Integrate agents with enterprise systems and data sources via Model Context Protocol (MCP) and standard APIs with strong attention to security observability reliability and cost controls.
Key Responsibilities
Develop high-scale microservices and APIs using Java 17 Spring Boot and REST/gRPC; apply solid engineering fundamentals (OOP concurrency performance).
Build Python services (e.g. FastAPI) that host agent logic and AI integrations; implement robust error handling retries and structured outputs.
Create and orchestrate agents using Google ADK: define agents attach tools/functions manage sessions and memory and implement multi-step workflows (sequential/parallel/routed).
Implement MCP-based integrations: expose internal tools/resources as MCP servers (where applicable) and consume MCP tools from agents/clients securely.
Deliver LLM features (tool/function calling prompt & context engineering evaluation) and implement RAG patterns with embeddings and vector databases when grounding is required.
Containerize and deploy services using Docker and Kubernetes (AKS/OCP preferred); build CI/CD pipelines (GitHub Actions/Jenkins/Harness) with quality gates.
Implement observability (logs/metrics/tracing) SLOs/SLIs and performance testing; participate in incident response and root cause remediation.
Mentor engineers perform design/code reviews and collaborate with product security data and platform teams in an Agile/Scrum environment.
Must-Have Skills
Strong Java backend engineering (Java 17 Spring Boot microservices REST/gRPC).
Strong Python engineering (OOP typing async patterns packaging) and service development.
Hands-on experience building agents and workflows with Google ADK (agents tools sessions/memory).
Comfort working with LLMs: tool/function calling structured outputs prompt & context engineering safety considerations.
Understanding of MCP concepts (resources tools prompts; client-server model) and ability to integrate tools using MCP or standard APIs.
Ability to produce high-quality code with AI-assisted code generation plus strong review/verification and testing discipline.
Security fundamentals: OAuth2/OIDC JWT secure coding secrets management; familiarity with mTLS/cert management is a plus.
Cloud-native fundamentals: Docker Kubernetes; CI/CD pipelines; basic monitoring/observability.
Good-to-Have Skills
LangChain/LangGraph or similar orchestration frameworks; experience combining them with ADK where useful.
Vector DB experience and RAG evaluation practices.
GCP/Vertex AI (or other cloud LLM hosting) and production deployment patterns (Cloud Run/Agent Engine).
Kafka/Flink or event-driven architectures for real-time systems.
Front-end exposure (React/Angular) for agent-driven UIs or developer tooling.
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