Agentic AI Lead Architect

About the Role

• We are seeking a highly skilled AI Engineer to join our team and drive innovation in Generative AI,
• Natural Language Processing (NLP), and Agentic AI. This role focuses on building production-grade
• agentic AI systems leveraging large language models. The AI Engineer will own the development of
• agent-to-agent architectures, LangGraph workflows, MCP-based state management, and OpenAI SDK
• integration to deliver scalable, business-ready AI applications that transform user experiences and
• business processes.

What Youll Do

• Design and implement advanced multi-agent, agent-to-agent AI architectures that enable
• autonomous and coordinated workflows.
• Build and manage LangGraph for building agentic framework.
• Develop and maintain agent to agent communication framework.
• Architect and implement robust Retrieval-Augmented Generation (RAG) pipelines, including
• document chunking, embedding generation, and retrieval evaluation to enhance knowledge
• access.
• Implement comprehensive guardrails, observability tools, and fallback mechanisms to ensure
• system resilience, reliability, and safe operation.
• Optimise AI systems for low latency, high reliability, scalability, and cost efficiency, suitable
• for production environments.
• Build and operate cloud-native services on AWS/Azure/GCP/IBM, leveraging managed
• services, IaC, containerisation (Docker), and orchestration (Kubernetes) where appropriate.
• Collaborate on API design and integration, working with Node.js services (e.g.,
• Express/NestJS) to expose and consume REST/GraphQL endpoints for agent workflows.
• Collaborate with cross-functional teams to integrate AI agents with large language models
• (LLMs), enabling dynamic decision-making and context-aware workflows.
• Apply expertise in NLP and transformer architectures to engineer intelligent conversational
• agents that deliver seamless interactions.
• Stay current with emerging trends and technologies in Agentic AI, LangGraph, LangChain,
• and related frameworks to continuously innovate and improve system capabilities.

Must-Have Skills

• Agentic AI Frameworks:
• Hands-on experience designing, building, and maintaining agentic AI systems using
• frameworks such as LangGraph/openAI SDK, with strong knowledge of agent-to-agent
• communication patterns.
• Programming:
• Strong Python skills with emphasis on asynchronous programming to develop scalable,
• production-grade AI systems.
• Distributed Systems:
• Solid understanding of distributed system fundamentals, enabling robust deployment and
• scaling of AI architectures.
• Cloud:
• Proven experience developing AI applications in cloud environments (AWS, Azure, GCP, IBM
• Cloud), ensuring reliability, scalability, and security.

Nice-to-Have Skills

• Foundational ML & Statistics:
• Basic knowledge of machine learning concepts and statistics sufficient for collaborating with
• data science teams and understanding model behaviour.
• Frontend/API Integration:
• Experience with frontend frameworks or API development (e.g., Node.js, React.js) to support
• integration of AI systems into user-facing applications.
• Domain Knowledge:
• Familiarity with finance, banking, or enterprise systems to better align AI solutions with
• business needs