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Job Description:

Role: Lead Agentic AI Developer

Location : Sydney

Lead the design and development of AI agents using Google Agentic Development Kit (ADK), defining agent architectures, tool integrations, and conversation flows

- Build and maintain backend services using FastAPI and FastMCP,



implementing MCP (Model Context Protocol) servers that expose tools and capabilities to agents
- Plan, track, and progress development activities across the agentic AI and integration layers, managing the complete lifecycle of features from conception through to production delivery
- Architect and implement agent-to-service communication patterns, including SSE streaming, async workflows, and inter-layer integrations
- Articulate technical requirements for agent behaviors, tool definitions, and service integrations at a detailed level, creating testable specifications and acceptance criteria
- Coordinate testing activities for agent systems, including prompt validation, tool execution verification, and end-to-end conversation flows
- Manage delivery of integrations between the agentic layer, backend services, and frontend UI, ensuring robust error handling and observability
- Act as technical liaison between AI/ML stakeholders and engineering teams, translating business requirements into agent capabilities and service architectures
- Oversee platform maintenance including agent prompt tuning, service optimization, database migrations, and infrastructure updates
- Mentor developers on agentic AI patterns, Python async best practices, and MCP protocol implementations
- Drive observability and monitoring strategies for agent performance,



tool execution latency, and system reliability

Agentic AI & LLM Systems

- Experience in using Agentic Coding Assistants (such as Claud Code, Copilot, etc)
- Deep understanding of LLM-based agent architectures, including tool use, multi-turn conversations, and state management
- Proficiency with Google Agentic Development Kit (ADK) or similar agent frameworks (LangChain, AutoGen, CrewAI)
- Experience designing and implementing Model Context Protocol (MCP) servers and tools using FastMCP
- Strong prompt engineering skills and understanding of LLM capabilities, limitations, and safety considerations
- Knowledge of RAG (Retrieval Augmented Generation), semantic search, and vector database patterns
- Expert-level Python 3.14+ development with up-to-date async patterns (asyncio, async/await)
- Strong experience with FastAPI 0.115+ for building high-performance REST APIs and SSE streaming endpoints
- Proficiency with SQLAlchemy 2.0+ (async mode) and asyncpg for database operations
- Experience with database schema design, migrations (Alembic), and optimization for PostgreSQL 16+
- Understanding of authentication/authorization patterns (JWT, OAuth2)
- Familiarity with httpx for async HTTP client operations Cloud & Infrastructure
- Experience with Google Cloud Platform (GCP): Cloud SQL, Cloud Storage, IAM, and containerized deployments
- Proficiency with Docker and Docker Compose for local development and service orchestration
- Understanding of CI/CD pipelines, automated testing, and DevOps practices
- Knowledge of observability tools (structured logging, metrics, tracing) and telemetry patterns
- Functional understand

📌 Lead Agentic AI Developer (Sydney)
🏢 Tata Consultancy Services
📍 Sydney