Principal Engineering Architect Agentic AI

Description

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.