Senior AI Engineer – Agentic AI & RAG

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 modern 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