Intermediate AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsonx

UPS; Chennai District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading logistics company is seeking an experienced AI Engineer with over 5 years of experience in software development and machine learning. The role involves designing and deploying AI systems, including LLMs and RAG implementations. Ideal candidates will have strong programming skills in Python, familiarity with AI protocols, and experience with frameworks such as LangChain and OpenAI. This position is committed to equality and inclusion in the workplace, reflecting the company's core values.

Qualifications

• 5+ years overall experience in software development, data science, or machine learning.
• 1+ year of hands-on experience developing AI applications with LLMs.
• 1+ year of experience with frameworks like LangChain.

Responsibilities

• Design, build, and deploy agentic AI systems using relevant frameworks.
• Develop multi-agent systems capable of autonomous decision-making.
• Implement and optimize retrieval-augmented generation systems.

Skills

Python programming

SQL basics

LLM/SLM APIs

RAG systems

LangChain

Google Cloud Platform (GCP)

Education

Bachelor’s degree in Computer Science or related field

Master’s or Ph.D.

Tools

LangGraph

OpenAI APIs

Job description

Job Summary

We are seeking a highly skilled AI Engineer with 5+ years of overall experience in software development, Data Science, or Machine Learning to design, develop, and deploy cutting‑edge AI systems leveraging Large Language Models (LLMs), Chatbots, Retrieval‑Augmented Generation (RAG), and agentic AI architectures.

Responsibilities

• Design, build, and deploy agentic AI systems using frameworks such as LangChain, LangGraph, and related libraries.
• Develop and deploy multi‑agent systems capable of autonomous decision‑making, reasoning, planning, and collaboration.
• Implement and optimize retrieval‑augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.
• Fine‑tune and prompt‑engineer LLMs for task‑specific reasoning, planning, and dynamic adaptation.
• Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.
• Lead the development of enterprise‑grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.
• Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.
• Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.
• Rapidly prototype, experiment, and iterate to improve AI agent capabilities.
• Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.
• Collaborate effectively with other engineers, researchers, and data scientists.
• Contribute to the documentation and standardization of technical code and practices.

Required Education

Master’s or Ph.D. is a strong plus. Bachelor’s degree in Computer Science, Engineering, or a related quantitative field.

Required Experience

• 5+ years overall experience in software development, data science, or machine learning.
• 1+ year of hands‑on experience developing AI applications with LLMs and systems such as retrieval‑based methods, fine‑tuning, or agent‑based architectures.
• 1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.

Required Technical Skills

• Strong programming skills in Python and basics in SQL.
• Expertise with LLM/SLM APIs, embeddings, and RAG systems.
• Experience deploying on Google Cloud Platform (GCP) with Vertex AI, and IBM WatsonX.
• Familiarity with agentic AI protocols and exposure to Agent Development Kits (ADKs).

Preferred Qualifications

• Experience implementing Model Context Protocol (MCP) for agent coordination.
• Prior exposure to LangGraph, AutoGen, or related orchestration frameworks.
• Knowledge of MLOps best practices (CI/CD for ML, observability, monitoring, scaling).
• Familiarity with responsible AI principles (safety, fairness, interpretability).
• Experience in enterprise‑scale deployments of AI‑driven platforms.
• Contributions to open‑source AI/ML projects are a plus.

Contract Type

en CDI

Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés.