AI Research Engineer

Zycus is a global leader in Source-to-Pay (S2P) procurement software, helping large enterprises drive efficiency, compliance, and measurable value across their procurement and finance operations. Trusted by leading Fortune 1000 organizations worldwide, Zycus enables procurement teams to move from cost control to strategic value creation.

At the core of Zycus’ platform is Merlin AI, an advanced AI-powered engine that brings intelligence, automation, and predictive insights across the entire procurement lifecycle—from sourcing and contract management to procurement, invoicing, and supplier management. Merlin AI empowers Chief Procurement Officers and finance leaders to make faster, smarter decisions with real-time visibility and actionable insights.

Zycus is consistently recognized by top industry analysts such as Gartner, Forrester, and IDC for its innovation, depth of functionality, and strong customer outcomes. Known for its enterprise-grade solutions, global delivery model, and customer-first mindset, Zycus partners closely with organizations to modernize procurement and unlock long-term business value.

With a strong global presence across North America, EMEA, and APAC, Zycus continues to invest aggressively in product innovation, AI-led capabilities, and brand leadership—shaping the future of intelligent procurement.

We Are An Equal Opportunity Employer:
Zycus is committed to providing equal opportunities in employment and creating an inclusive work environment. We do not discriminate against applicants on the basis of race, color, religion, gender, sexual orientation, national origin, age, disability, or any other legally protected characteristic. All hiring decisions will be based solely on qualifications, skills, and experience relevant to the job requirements.

At Zycus, we believe the next generation of enterprise software will not be powered by workflows—it will be powered by intelligent AI agents.

We are building an enterprise-grade Agentic AI Platform capable of autonomous reasoning, planning, collaboration, memory, learning, and execution at scale. This platform will power procurement transformation for some of the world's largest organizations.

We're looking for exceptional engineers and researchers who want to solve difficult AI systems problems—not just integrate APIs.

If you enjoy reading research papers, building new algorithms, experimenting with frontier models, and turning research into production systems, we'd love to talk to you.

What You'll Build

You will help design and develop the core technology behind Zycus' Agentic AI Platform, including:

• Autonomous AI Agents

• Multi-Agent Collaboration Frameworks

• Agent Memory Systems

• Planning & Reasoning Engines

• Enterprise Knowledge Graphs

• Retrieval-Augmented Generation (RAG)

• Long-term Memory Architectures

• Tool-use Frameworks

• Workflow Orchestration

• Model Evaluation Platforms

• AI Safety & Guardrails

• AI Observability

• Agent Benchmarking Frameworks

Your work will directly influence how enterprise AI evolves over the next decade.

What You'll Do

Research

• Read and implement cutting-edge AI research

• Reproduce state-of-the-art techniques from leading conferences and journals

• Evaluate emerging foundation models and reasoning architectures

• Prototype new ideas rapidly and validate them through experimentation

Engineering

• Convert research into production-grade software

• Build scalable AI infrastructure and services

• Design APIs, SDKs, and reusable AI platform components

• Optimize latency, cost, and reliability of AI systems

AI Systems

Work on problems such as:

• Agent planning

• Multi-agent coordination

• Tool selection

• Context engineering

• Model routing

• Memory management

• AI evaluation

• Autonomous decision-making

• Reinforcement learning from feedback

• Long-context reasoning

• Semantic retrieval

• Knowledge representation

Experimentation

Design rigorous experiments to improve:

• Accuracy

• Reliability

• Hallucination reduction

• Agent success rates

• Cost efficiency

• Planning quality

• Benchmark performance

Who We're Looking For

We're far more interested in exceptional problem-solving ability than years of experience with a specific framework.

You might be a great fit if you have:

• M.Tech or PhD in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Computational Linguistics, or a related discipline

• Outstanding software engineering skills in Python

• Strong foundations in algorithms, distributed systems, and software architecture

• Deep understanding of machine learning and modern AI techniques

• Curiosity to explore frontier AI research

• Ability to translate research ideas into working systems

Fresh PhDs and outstanding M.Tech graduates with exceptional research work are encouraged to apply.

Preferred Background

Experience in one or more of the following:

• Large Language Models

• Agentic AI

• Reinforcement Learning

• NLP

• Deep Learning

• Search

• Information Retrieval

• Knowledge Graphs

• Distributed Systems

• Probabilistic Reasoning

• Planning Algorithms

• Multi-Agent Systems

• Robotics AI

• Cognitive Architectures

Technologies You May Work With

• Python

• PyTorch

• JAX

• Hugging Face

• vLLM

• Ray

• LangGraph

• DSPy

• LlamaIndex

• Kubernetes

• Docker

• Vector Databases

• Graph Databases

• MCP

• FastAPI

• GPU Computing

Experience with these tools is valuable but not mandatory. Strong fundamentals matter more than familiarity with any specific framework.

What Makes Someone Exceptional

We would be excited if you have:

• Publications in NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, or similar conferences

• Open-source AI contributions

• Research internships

• Kaggle or AI competition achievements

• Experience building AI systems from scratch

• Strong mathematical foundations

• Curiosity to challenge existing approaches

Why Join Zycus?

• This is not another application engineering role.

• You will help invent the core AI platform that powers autonomous enterprise software.

• You'll work on frontier AI problems including reasoning, planning, memory, multi-agent systems, and autonomous decision-making—taking ideas from research papers to production.

• If your ambition is to build technology that defines the next generation of enterprise AI rather than simply consume existing APIs, this is the place to do it.