Artificial Intelligence Engineer

We are done talking about AI hype—we are building the reality. Terralogic is assembling an elite, core AI squad in Bangalore to build the brain of our next-generation enterprise systems. We are looking for an engineer with 3 to 6 years of experience pushing production code who is ready for an immersive, 5-day-a-week, on-site collaboration model where innovation moves fast. We are not looking for prompt engineers or tutorial followers. We need a brilliant AI Engineer who lives to design, build, and deploy intelligent agents that actually solve complex, real-world problems.

If you want your code to impact massive enterprise workflows rather than sitting in a sandbox, this is your playground.

What You Will Do

• Architect RAG Pipelines: Design and implement robust Retrieval-Augmented Generation pipelines for enterprise impact.
• Build Autonomous Agents: Create, optimize, and deploy advanced AI agents using LangGraph, AutoGen, or similar frameworks.
• Scale in Production: Own the lifecycle of scalable AI solutions from local prototype to cloud production.
• Collaborate and Integrate: Partner directly with Design, Product, and Engineering teams to embed intelligence into core applications.
• Innovate Constantly: Research, prototype, and test the newest LLM techniques to keep our systems ahead of the curve.

What You Bring

• The Foundation: A Master’s degree in CS, AI, ML, or a related field (preferred).
• Code Craftsmanship: Strong backend development skills (Python, APIs, microservices, cloud deployment).
• AI Expertise: Deep familiarity with LLMs, vector databases, embeddings, and orchestration frameworks.
• Proven Track Record: Experience building and scaling real-world AI applications, not just tutorial projects.
• The Ecosystem: Hands-on experience with LangChain, LangGraph, AutoGen, or equivalent tools.
• Engineering Discipline: A solid grasp of data pipelines, MLOps, and rigorous evaluation metrics.

Bonus Points for:

• Open-source contributions to AI frameworks.
• Experience with distributed systems and heavy data processing.
• Knowledge of reinforcement learning or advanced ML research.

Our Interview Process (Direct & Transparent)

You will work directly with your future interviewer throughout both stages of our streamlined technical process:

1. The Technical Screen & Challenge: We review your profile against this blueprint. If it is a match, you will get a real-world problem statement to design an optimized architecture for a specific use case.
2. The Architecture Presentation: You will present your architectural solution directly to the interviewer, showcasing your design choices, trade-offs, and engineering logic.