Live opening · Posted 20 days ago
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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
Work arrangement
No
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