Developer/ Leads

Senior Developer/ Leads with Java, Python + Google ADK, comfortable working with LLMs, MCP, building Agents, generating code, · 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.

· 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., · 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

· 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.

· Google Cloud Platform/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.