Role Overview :

As a Senior Agentic AI Engineer based in Bangalore, you will spearhead the design and deployment of sophisticated autonomous systems that transcend traditional LLM implementations. You will work at the intersection of product engineering and machine learning research, collaborating closely with cross-functional teams of data scientists, backend engineers, and product managers to translate complex business requirements into scalable agentic workflows. Your work will directly influence the efficiency of our internal operations and the quality of our customer-facing AI products, ensuring that our systems can reason, plan, and execute multi-step tasks with high reliability and minimal human intervention.

Key Responsibilities :

- Architect and implement complex multi-agent systems using LangGraph to automate intricate business processes and reduce manual operational overhead.

- Design and maintain robust RAG pipelines that provide agents with accurate, context-aware information to improve decision-making accuracy for end-users.

- Develop and scale custom tool-calling frameworks, enabling agents to interact seamlessly with diverse APIs and enterprise databases to perform real-world actions.

- Implement Model Context Protocol (MCP) standards to ensure interoperability across our AI ecosystem, facilitating smoother data exchange between disparate agentic services.

- Establish rigorous AI evaluation frameworks to measure agent performance, latency, and hallucination rates, ensuring high-quality outputs before production deployment.

- Optimize A2A (Agent-to-Agent) communication protocols to enhance coordination and task delegation within distributed multi-agent architectures.

Required Skillset :

- Demonstrated expertise in building and deploying Agentic AI solutions, with a deep understanding of state machines and graph-based orchestration frameworks like LangGraph.

- Proven ability to design scalable tool-calling architectures and integrate them into production-grade AWS environments, ensuring high availability and low latency.

- Strong proficiency in implementing RAG systems and advanced retrieval strategies that significantly enhance the reasoning capabilities of large language models.

- Exceptional problem-solving skills with the ability to communicate complex technical trade-offs to non-technical stakeholders and leadership teams.

- A collaborative mindset with the ability to thrive in a fast-paced, hybrid work environment in Bangalore, working alongside high-performing engineering teams.

- A solid foundation in computer science, typically evidenced by a degree in Engineering or a related quantitative field, coupled with a track record of delivering production-ready AI software over 5 - 8 years of professional experience.