Senior AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsox

UPS; Chennai District; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

A leading logistics company is seeking a skilled AI Engineer to design and deploy AI systems utilizing LLMs, Chatbots, and RAG architectures. Ideal candidates should have experience in developing AI applications and deploying solutions on Google Cloud Platform. The role involves responsibilities such as the development of multi-agent systems and contributing to MLOps practices. A bachelor’s degree in a relevant field and significant programming skills are required. Competitive compensation available.

Qualifications

• 5+ years of relevant experience in AI applications.
• Hands-on experience with LLMs and retrieval-based methods.
• Experience with frameworks like LangChain and LlamaIndex.

Responsibilities

• Design and build agentic AI systems.
• Implement RAG pipelines for knowledge integration.
• Lead AI platform development and MLOps best practices.

Skills

Strong programming skills in Python

Expertise with LLM/SLM APIs

Familiarity with SQL

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Google Cloud Platform (GCP)

Vertex AI

IBM WatsonX

LangChain

LlamaIndex

Job description

Job Summary

We are seeking a highly skilled AI Engineer experienced 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.

This role involves hands‑on development with LLMs, embeddings, RAG pipelines, and multi‑agent systems using modern frameworks like LangChain, LangGraph, and LlamaIndex. The ideal candidate has experience with Vertex AI on GCP and IBM WatsonX, fine‑tuning, and Agent Development Kits (ADKs), and is excited about building scalable, production‑grade AI platforms.

Responsibilities

• Agentic AI Development: Design, build, and deploy agentic AI systems using frameworks such as LangChain, LangGraph, and related libraries.
• Multi‑agent Systems: Develop and deploy multi‑agent systems capable of autonomous decision‑making, reasoning, planning, and collaboration.
• RAG Pipelines: Implement and optimise retrieval‑augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.
• LLM Engineering: Fine‑tune and prompt‑engineer LLMs for task‑specific reasoning, planning, and dynamic adaptation.
• Enterprise AI Platform: Lead the development of enterprise‑grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.
• Model Context Protocol (MCP): Implement and standardise MCP for consistent context management across models and agents.
• MLOps & Observability: Establish and enforce best practices for MLOps, monitoring and observability, ensuring scalable and maintainable AI solutions.
• Applied AI Prototyping: Rapidly prototype, experiment, and iterate to improve AI agent capabilities.
• Collaboration & Research: Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings; collaborate effectively with other engineers, researchers, and data scientists.
• Documentation & Standardisation: Contribute to the documentation and standardisation of technical code and practices.

Required Education

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

Required Experience

• Senior – Min 5+ years of relevant experience.
• Intermediate – Min 3+ years of relevant experience.
• Associate – Min 2+ years of relevant experience.
• 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 Lang Graph, 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.

Type De Contrat

en CDI

Equal Opportunity Statement

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