Senior AI Engineer – Agentic AI & RAG

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

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: Lang.

Chain Lang. Graph 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