Senior 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.

Do you have experience in gRPC?, 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 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.