Artificial Intelligence Engineer

About the RoleWe’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 DoBuildDesign, develop, and deploy AI-powered applications for real-world business problems using Python and modern AI frameworksBuild applications leveraging Generative AI, LLMs, NLP, and AI agents — including multi-step and tool-using agentic workflowsDesign and implement RAG (Retrieval-Augmented Generation) pipelines, including chunking, embedding, and vector database strategiesIntegrate pre-trained and foundation models (via APIs or self-hosted) into production applicationsProductionizeDevelop and integrate REST APIs and microservices around AI capabilitiesEvaluate, optimize, and monitor AI systems — accuracy, latency, cost, and safety — against business requirementsApply prompt engineering, guardrails, and evaluation frameworks to make LLM behavior reliable and auditableFollow strong engineering practices: system design, CI/CD, testing, and Git workflowsDeliverDrive end-to-end delivery of AI solutions — on time, within scope, and aligned to expected outcomesLead stakeholder engagement, change management, and user adoption to maximize business valueContinuously explore new models, frameworks, and patterns; bring back what’s worth adoptingBasic 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 applicationsMust-Have SkillsStrong programming skills in Python; working proficiency in TypeScript/JavaScriptHands-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 similarStrong understanding of RAG, embeddings, vector databases, prompt engineering, and AI agentsExperience with SQL and NoSQL databasesSolid grasp of API design, microservices, CI/CD pipelines, and Git workflowsFamiliarity with at least one cloud platform (AWS, Azure, or GCP) and containerization with DockerStrong communication and stakeholder management skills — able to work effectively across business and technical teamsNice-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