Sr AI Engineer (Startup/ Global Product)

Key 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.
• 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 59 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, etc.).
• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker,
• Kubernetes).
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Experience working in consulting or enterprise product environments (preferred).
• Bachelors or Masters degree in Computer Science, Data Science, AI, or a related field.