Senior AI Engineer (Startup/ Energy & Power/ 8+ years)

: • Design, train, fine-tune, and evaluate Generative AI models (LLMs, multimodal models) for enterprise use cases. • Develop and optimize prompt engineering, RAG pipelines, agents, and fine-tuning workflows. • Design, develop, and optimize a multi‑agent agentic framework that enables autonomous, domain‑aware collaboration across specialized agents. • Work with open-source and commercial LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.). • Implement guardrails, safety mechanisms, and hallucination mitigation techniques. • Partner with business, consulting, and product teams to identify, evaluate, and prioritize GenAI use cases. • Translate business problems into clear GenAI solution architectures and success metrics. • Create solution blueprints, prototypes, and POCs to demonstrate business value. • Design and manage data pipelines for AI training, fine-tuning, and inference. • Build scalable, secure, and cost-efficient GenAI systems for production environments. • Collaborate with engineering teams on deployment, monitoring, and retraining strategies. • Monitor model performance, latency, cost, and drift in production. • Ensure responsible, ethical, and compliant use of Generative AI. • Implement explainability, auditability, and traceability mechanisms where required. • Address data privacy, IP protection, and regulatory constraints (e.g., GDPR). • Define and enforce AI best practices, standards, and usage guidelines.

: • Prior 5–9 years of experience in data science, ML engineering, or AI development, with 2+ years focused on Generative AI. • Strong hands-on experience with LLMs, transformers, embeddings, and vector databases. • Proficiency in Python and GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face). • Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning). • Experience designing multi‑agent systems, including orchestration, coordination, and distributed reasoning. • Familiarity with MLOps tools, CI/CD pipelines, and model monitoring. • Familiarity with 3D deep learning and large scale point cloud processing is a plus. • Experience working in fast paced startup environment (preferred). • Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.