Principal Engineer – Agentic AI Platform

Zycus is building a next-generation Agentic AI Platform to autonomously execute enterprise procurement workflows. We are looking for a deeply hands-on, polyglot engineering leader with a strong foundation in Java/microservices who has evolved into building AI/LLM-driven systems in production . This role requires someone who can architect, build, and scale intelligent systems end-to-end , while being comfortable working across backend, frontend, and emerging AI technologies. Roles & Responsibilities Architect and build the core Agentic AI platform for Zycus Design and implement multi-agent systems (planning, reasoning, execution loops) Develop LLM-powered systems integrated with enterprise workflows (ERP, sourcing, contracts) Build agent orchestration frameworks (task decomposition, tool usage, memory, feedback loops) Develop and scale backend services using Java, Spring Boot, and microservices architecture Contribute across the stack including: API design and integrations Frontend interfaces (React / Angular / Node.js) for AI-driven workflows Ensure enterprise-grade reliability : Observability, monitoring, debugging AI systems Fallback mechanisms and auditability Optimize systems for performance, scalability, latency, and cost Build reusable platform components and developer frameworks Rapidly evaluate and adopt new AI and engineering technologies Mentor engineers and drive high engineering standards and best practices Skills, Experience & Education (Required) 1. Core Software Engineering Expertise 10+ years of experience building scalable software systems Strong hands-on expertise in: Java, Spring Boot Microservices and distributed systems architecture Proven experience building enterprise SaaS platforms 2. Polyglot & Full-Stack Capability Hands-on experience with one or more frontend technologies: React / Angular / Node.js Ability to work across the stack (backend, APIs, frontend) Demonstrated ability to quickly learn and adapt to new technologies 3. AI / LLM Systems Experience (Production-Grade) Hands-on experience building: LLM-powered applications in production Agentic workflows / multi-step AI systems Strong understanding of: RAG architectures Prompting, evaluation, and system design Model limitations (hallucination, latency, cost) 4. Agentic AI & System Design Experience with or strong understanding of: Multi-agent frameworks (LangGraph, AutoGen, CrewAI, or similar) Tool-integrated AI systems (APIs, workflows, enterprise systems) Memory, orchestration, and feedback mechanisms Ability to design end-to-end intelligent systems , not just integrations 5. Hands-On Builder Mindset Actively writes production-quality code Strong problem-solving and system design capabilities Experience owning systems end-to-end (design → build → scale) 6. Enterprise Engineering Rigor Experience building systems with: High scalability, reliability, and performance Observability and debugging frameworks Understanding of: Security, data privacy, and governance in AI systems 7. Education Bachelor’s or Master’s degree in Computer Science / Engineering or related field Candidates from top engineering institutes (IITs, NITs, IIITs, or global equivalents) preferred What This Role Is NOT Not a Data Scientist role Not a pure research role Not a people management-only role This is a hands-on engineering leadership role for builders who can work across technologies and define the future of enterprise AI systems .