AI Engineer

About the Role

We’re building AI solutions that solve real enterprise problems — not demos, not proofs-of-concept that die in a slide deck, but production systems that ship and scale. We’re looking for an AI Engineer ready to take true ownership: from framing a business problem, through designing and building the solution, to seeing it adopted by real users.
You’ll design, develop, and deploy AI-powered applications using Generative AI, LLMs, agentic frameworks, and modern data infrastructure. You’ll partner with cross-functional teams to turn complex business challenges into working software — and continuously push on performance, reliability, and user experience.

What You’ll Do

Build

• Design, develop, and deploy AI-powered applications for real-world business problems using Python and modern AI frameworks
• Build applications leveraging Generative AI, LLMs, NLP, and AI agents — including multi-step and tool-using agentic workflows
• Design and implement RAG (Retrieval-Augmented Generation) pipelines, including chunking, embedding, and vector database strategies
• Integrate pre-trained and foundation models (via APIs or self-hosted) into production applications

Productionize

• Develop and integrate REST APIs and microservices around AI capabilities
• Evaluate, optimize, and monitor AI systems — accuracy, latency, cost, and safety — against business requirements
• Apply prompt engineering, guardrails, and evaluation frameworks to make LLM behavior reliable and auditable
• Follow strong engineering practices: system design, CI/CD, testing, and Git workflows

Deliver

• Drive end-to-end delivery of AI solutions — on time, within scope, and aligned to expected outcomes
• Lead stakeholder engagement, change management, and user adoption to maximize business value
• Continuously explore new models, frameworks, and patterns; bring back what’s worth adopting

Basic Qualifications

• Education: B.E. / B.Tech / M.Sc. / M.E. / M.Tech in Computer Science, Engineering, or a related field
• Experience: 3+ years in AI/ML engineering, with at least 1 year building LLM/GenAI applications
• Must-Have Skills
• Strong programming skills in Python; working proficiency in TypeScript/JavaScript
• Hands-on experience with LLM APIs and foundation models (OpenAI, Anthropic, Gemini, or open-weight models)
• Experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, or similar
• Strong understanding of RAG, embeddings, vector databases, prompt engineering, and AI agents
• Experience with SQL and NoSQL databases
• Solid grasp of API design, microservices, CI/CD pipelines, and Git workflows
• Familiarity with at least one cloud platform (AWS, Azure, or GCP) and containerization with Docker
• Strong communication and stakeholder management skills — able to work effectively across business and technical teams

Nice-to-Have Skills

• Model fine-tuning and evaluation (LoRA/PEFT, evals frameworks)
• Kubernetes and infrastructure-as-code
• MLOps / LLMOps tooling (experiment tracking, model registries, observability)
• Data engineering on modern platforms (Databricks, Snowflake, or equivalent)
• C++ or other systems-level programming experience
• Exposure to responsible AI practices: guardrails, red-teaming, PII handling