Lead AI Agent Developer

Role description

Experience: 5–8 Years

Employment Type: Full-time

Job Summary

We are looking for an experienced AI Agent Developer with strong expertise in building, deploying, and monitoring AI agents using the LangChain ecosystem. The ideal candidate should have hands-on experience in developing agentic AI applications, implementing orchestration workflows, evaluating LLM performance, and deploying production-ready AI solutions. The role requires proficiency in Python, Databricks, SQL, and modern AI agent frameworks such as LangChain, LangGraph, and LangSmith.

Key Responsibilities

Design, develop, and deploy AI agents using LangChain and LangGraph.

Build stateful, multi-agent workflows with memory, tool integration, and human-in-the-loop capabilities.

Develop Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases and embeddings.

Utilize LangSmith for tracing, debugging, observability, automated testing, and evaluation of AI agents.

Create evaluation datasets and implement automated testing frameworks to measure LLM performance and reduce regressions.

Optimize prompts, reasoning workflows, and agent performance through continuous experimentation and monitoring.

Deploy, monitor, and maintain AI agents in production environments.

Build dashboards and s to monitor latency, cost, response quality, and hallucination rates.

Collaborate with cross-functional teams to integrate AI agents into enterprise applications.

Follow best practices for AI application development, testing, deployment, and monitoring.

Mandatory Skills

5+ years of software engineering experience, including 2+ years of hands-on experience in LLM/Generative AI application development.

Strong proficiency in Python.

Hands-on experience with LangChain for building and deploying AI agents.

Strong expertise in LangGraph for developing multi-agent orchestration workflows.

Experience with LangSmith for observability, tracing, debugging, evaluations, and prompt testing.

Strong understanding of LLM application development, including prompt engineering, RAG, embeddings, vector databases, tool calling, memory management, and agent orchestration.

Experience working with Databricks and MS SQL.

Experience deploying, monitoring, and optimizing AI agents in production environments.

Strong analytical, debugging, and problem-solving skills.

Good-to-Have Skills

Experience in the Payments/Financial Services domain.

Experience with cloud platforms (Azure, AWS, or GCP).

Knowledge of AI model evaluation frameworks and LLMOps best practices.

Experience working in Agile/Scrum environments.

Preferred Candidate Profile

Experience developing enterprise-scale AI agent solutions.

Strong understanding of AI agent lifecycle: Build Test Evaluate Deploy Monitor.

Passion for building reliable, scalable, and production-ready Generative AI applications.

Excellent communication and collaboration skills.

Skills

Agentic AI, LLMs, LangChain, LangGraph, LangSmith, Databricks, Observability, Python, RAG, Vector Databases

About UST

UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients’ organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact - touching billions of lives in the process.