Your responsibilities:

▪ Lead the design and implementation of complex multi-step reasoning chains and agentic RAG pipelines using LangGraph and structured output patterns.

▪ Architect and enforce safeguard mechanisms including prompt injection defence, hallucination mitigation, and context-window management across all AI agents.

▪ Integrate AI components with the Model Context Protocol (MCP) to ensure agents access a shared, grounded knowledge base with reliable and auditable outputs.

. ▪ Continuously evaluate and optimise prompt strategies, retrieval mechanisms, and model configurations to improve agent accuracy, latency, and reliability at enterprise scale.

Your profile:

▪ Bachelor's or Master's degree in Computer Science, AI, or a related field, with 5+ years of hands-on experience building production AI/ML systems.





▪ Expert-level Python programming skills with deep practical experience in LangGraph, agentic RAG architectures, and structured output design patterns.

▪ Proven ability to implement AI safety and quality mechanisms including prompt injection defence, hallucination mitigation, and context-window management in production environments.

▪ Solid understanding of the Model Context Protocol (MCP), LLM orchestration patterns, and foundation models such as Anthropic Claude.

▪ Solid experience with CI/CD integration, containerisation (Docker/Kubernetes), and DevSecOps practices in cloud environments (GCP preferred).

Pay: ₹1,500,000.00 - ₹4,500,000.00 per year

Work Location: In person

📌 Applied AI Engineer (India)
🏢 Task Staffing
📍 India