AI Engineer

T-Systems ICT India Pvt. Ltd.; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

T-Systems ICT India Pvt. Ltd. is looking for an experienced AI Engineer in Bengaluru, India. The selected candidate will design and deploy AI-powered solutions that automate workflows and enhance decision-making.

This position demands strong expertise in Large Language Models (LLMs), cloud platforms, and integrating AI models with enterprise systems. Applicants should have 7-10 years of experience in AI and machine learning.

Qualifications

• 7-10 years of experience in AI and machine learning.
• Proficiency in building AI applications using LLMs.
• Experience with integration of AI models and enterprise systems.

Responsibilities

• Design and develop AI and machine learning solutions using LLMs.
• Build AI-driven applications including chatbots and automation tools.
• Integrate AI models with enterprise systems and workflows.

Skills

Large Language Models (LLMs)

Machine Learning

Cloud Platforms (Azure, AWS, GCP)

Data Pipelines

APIs

Tools

LangChain

LangGraph

Databricks

Job description

Role Summary

We are seeking an experienced AI Engineer to design, build, and deploy AI‑powered solutions that automate workflows, enhance decision‑making, and integrate seamlessly with enterprise systems. This role involves working with Large Language Models (LLMs), APIs, data pipelines, and cloud platforms to deliver production‑grade AI applications. Experience required 7‑10 years.

Key Responsibilities

• Design and develop AI and machine learning solutions using Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or similar platforms.
• Build AI‑driven applications including chatbots, copilots, intelligent agents, and automation tools.
• Integrate AI models with enterprise systems, APIs, databases, and workflows.
• Implement advanced techniques including prompt engineering, Retrieval Augmented Generation (RAG), and vector search capabilities.
• Develop and deploy AI services using cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
• Leverage frameworks and tools including LangChain, LangGraph, and Databricks for AI development and deployment.