AI Engineer (Startup/ 3-5 years)

Responsibilities

• 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.

Good to have

• Prior 3-5 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.