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