Agentic AI Engineer (02 Years Experience)

Location: Pune India

About the Role

We are looking for an early-career Agentic AI Engineer to help build and evolve AI-powered systems that automate and improve supply chain this role youll work alongside experienced engineers and data scientists to develop agentic AI / GenAI features integrate knowledge-based retrieval (RAG) patterns and contribute to testing and validation approaches for AI systems that can behave in non-deterministic ways.

This is a strong opportunity for someone who is eager to grow in both software engineering and applied GenAI and wants to work on real-world enterprise problems in supply chain and (optionally) life sciences.

Key Responsibilities

• Support the design and implementation of agentic AI / GenAI systems that assist in automating supply chain workflows.

• Build and maintain backend services and integrations using Python and/or Java.

• Contribute to multi-agent workflows such as tool execution routing agent collaboration patterns and task orchestration.

• Assist in creating testing and validation strategies for AI systems including evaluation datasets regression testing and behavior monitoring.

• Help implement and improve knowledge base systems including RAG pipelines grounding strategies and retrieval quality improvements.

• Contribute to experimentation with:

  • lightweight fine-tuning approaches for small language models (SLMs)

  • reinforcement-learning-inspired improvement loops for NLP/GenAI tasks (where applicable)

• Partner with product and domain teams to understand supply chain needs and translate them into working software.

• Participate in code reviews documentation and operational support to ensure high-quality production systems.

Required Qualifications

• Masters degree in Data Science Artificial Intelligence Machine Learning Computer Science or a closely related discipline.

• 02 years of professional experience in software engineering AI engineering or ML engineering (internships and co-ops count).

• Strong programming skills in Python and/or Java including writing production-quality code.

• Familiarity with cloud platforms such as AWS GCP or Azure (academic personal or internship experience is acceptable).

• Interest or exposure to Generative AI concepts such as LLMs agent workflows tool calling or multi-step reasoning.

• Understanding of core engineering fundamentals:

  • APIs and services

  • basic distributed systems concepts

  • debugging and performance basics

  • data structures & algorithms

• Ability to learn quickly take feedback well and collaborate effectively in a team environment.

Preferred Qualifications

• Coursework projects or hands-on experience with agentic or multi-step AI systems including non-deterministic behavior patterns.

• Exposure to designing knowledge base solutions such as:

  • Retrieval-Augmented Generation (RAG)

  • embedding-based search

  • hybrid search approaches

  • reranking or relevance evaluation

• Experience or academic background in one of the following:

  • fine-tuning small language models (SLMs)

  • training or adapting NLP models

  • Reinforcementreinforcement learning concepts applied to language systems

• Exposure to event-driven or reactive systems

• Interest in supply chain domains (logistics manufacturing procurement etc.).

• Knowledge of the life sciences supply chain is a plus but not required.

What Success Looks Like

• You can take a defined task (e.g. building a new RAG retriever improving evaluation coverage or implementing a new agent tool) and deliver a working solution with support from senior engineers.

• You write clean testable code and steadily improve your ability to debug real-world production issues.

• You contribute to AI system reliability through experiments evaluation improvements and thoughtful engineering.

Who You Are

• Curious motivated and excited to build AI-driven products that ship to real users.

• Comfortable working with a mix of predictable engineering tasks and emerging AI workflows.

• Strong team player with a growth mindset and a willingness to learn.