Role Description Job Summary

We are looking for an AI Engineer with deep experience in building agent-based AI applications . This role is ideal for someone passionate about pushing the boundaries of applied AI, particularly in Retrieval-Augmented Generation (RAG) , and developing production-grade intelligent systems that are secure, governed, and enterprise-ready .

Key Responsibilities

AI / LLM Engineering

- Design, develop, and deploy agent-based AI systems using LLMs.
- Build and scale Retrieval-Augmented Generation (RAG) pipelines for real-time and offline inference.
- Develop and optimize training workflows for fine-tuning and adapting models to domain-specific tasks.
- Collaborate with cross-functional teams to integrate knowledge bases into agent frameworks.
- Drive best practices in AI Engineering, model lifecycle management, and production deployment on Google Cloud (GCP).
- Monitor, evaluate, and improve model performance post-deployment on Google Cloud.

DevOps / MLOps
- Implement version control strategies using Git, manage code repositories, and ensure best practices in code management.
- Develop and manage CI/CD pipelines using GitHub Actions, Jenkins, or other relevant tools to streamline deployment and updates.

Security & Identity
- Secure AI application front-ends and user interfaces by integrating them with enterprise Single Sign-On (SSO) and Multi-Factor Authentication (MFA)



using:

- OIDC
- OAuth 2.0

- SAML
- Integrate AI agent frameworks and service accounts with enterprise IGA platforms to automate:

- Access provisioning

- Entitlements

- Compliance auditing

Collaboration
- Communicate technical findings and insights to non-technical stakeholders.
- Participate in technical discussions and contribute to strategic planning.

Qualifications Education
- Master’s / Bachelor’s degree in:

- Computer Science

- Artificial Intelligence

- Machine Learning

- Or a related field

Experience
- 10+ years of overall IT experience.
- 5+ years of AI/ML Engineering experience, with a strong focus on LLM-based applications.
- Proven experience building agent-based applications using Gemini, OpenAI, or similar models.

- Deep understanding of

- RAG systems

- Vector databases

- Knowledge retrieval strategies
- Hands-on experience with:

- LangChain

- LangGraph

- Solid background in

- Model training
- Fine-tuning

- Evaluation

- Deployment
- Strong coding skills in Python.
- Experience with up-to-date MLOps practices.

- Experience managing

- Service accounts

- IAM roles

- Secret management tools

- GCP IAM

- Vertex AI security

Skills AI/ML, Gen AI, LLM, RAG, LangChain, LangGraph, Python, GCP/Vertex AI

📌 Senior AI Engineer – Agentic AI & RAG (Thiruvananthapuram)
🏢 UST
📍 Thiruvananthapuram