AI Engineer

Zensar Technologies Limited is seeking a forward‑thinking AI Engineer to join our innovative team. You will work with our enterprise AI stack to build cutting‑edge applications, proof‑of‑concepts, and intelligent multi‑agent systems that drive business value. The role involves end‑to‑end development, from model integration and prompt engineering to CI/CD deployment and observability, while collaborating across functions to ensure alignment with strategic objectives.
Hands‑on experience integrating LLMs (e.g., GPT, Gemini) and prompt engineering.
Proficiency with LangGraph and LangSmith for building AI workflows and agents.
Experience with agent builder platforms, multi‑agent systems, and orchestration.
Familiarity with Model Context Protocol (MCP), MCP Tools, and A2A communication.
Strong programming skills in Python and familiarity with AI/ML libraries (e.g., PyTorch, TensorFlow).
Knowledge of vector databases, embeddings, and RAG architectures.
Experience with CI/CD tools (e.g., Jenkins, GitHub Actions) and monitoring/observability solutions.
Bachelor’s or higher degree in Computer Science, AI, Machine Learning, or related field.
Excellent problem‑solving abilities and a collaborative mindset.
Ability to work in an agile environment and manage multiple priorities.
Design, develop, and deploy AI‑powered applications using Zensar's enterprise AI stack.
Build and execute proof‑of‑concepts (POCs) with Large Language Models (LLMs) and modern AI orchestration tools.
Create intelligent agents and multi‑agent systems using LangGraph and agent builder platforms.
Implement Model Context Protocol (MCP) integrations, MCP Tools, and agent‑to‑agent (A2A) communication patterns.
Leverage vector stores, embeddings, and Retrieval‑Augmented Generation (RAG) architectures.
Manage source code through CI/CD pipelines and ensure observability of AI applications.
Contribute to and maintain the internal agent registry and integration standards.
Perform prompt engineering and fine‑tuning for GPT, Gemini, and other LLMs.
Collaborate with cross‑functional teams to align AI solutions with business objectives.
Document designs, workflows, and best practices for AI development.