Your responsibilities:
▪ Architect and implement multi-agent orchestration patterns using LangGraph, designing skills-based workflows that power the Refinement, Decision, and Coding Agents across the Agent Chain platform.
▪ Design and evolve prompting architectures and RAG strategies that achieve highfidelity, reliable AI outputs grounded in application-specific knowledge bases via Model Context Protocol (MCP).
▪ Conduct technical design reviews and establish engineering best practices for AI service development, ensuring compliance with EU AI Act, DORA, and internal DevSecOps standards.
▪ Evaluate and benchmark foundation models (Claude, GPT, Gemini) for specific agent tasks, optimising for accuracy, latency, and cost across the agent pipeline.
Your profile:
▪ Bachelor's or Master's degree in Computer Science, AI, or a related field, with 5+ years of experience building AI/ML systems and at least 2 years working with LLMbased applications in production.
▪ Expert-level Python programming skills with hands-on experience in LangGraph, LangChain, and modern AI orchestration frameworks for building multi-agent systems.
▪ Deep expertise in prompt engineering, RAG architectures, and agentic workflow design, with a proven track record of delivering high-quality, reliable AI outputs at scale.
▪ Strong working knowledge of foundation models (Anthropic Claude, OpenAI GPT, Google Gemini) including fine-tuning strategies, context window management, and model evaluation methodologies.
▪ Demonstrated ability to lead technical discussions, and drive engineering standards within a distributed, cross-time zone team.
Pay: ₹1,400,000.00 - ₹4,500,000.00 per year
Work Location: In person
