Job Description

Senior AI Engineer – Data Science & Generative AI

Mission Build and productionize intelligent AI systems — combining deep data science expertise with engineering rigor to deliver scalable Gen AI solutions.

What You'll Do

• Design and build end-to-end Gen AI and ML pipelines - from data exploration to production deployment
• Develop agentic AI systems: RAG, tool orchestration, planning/execution flows
• Build retrieval services, embedding pipelines, and model-routing infrastructure
• Train, fine-tune, and evaluate LLMs and ML models; implement monitoring and cost-control frameworks
• Translate data science research into robust, production-grade services
• Collaborate with Engineering and Product; contribute to AI architecture decisions

Requirements

What We're Looking For

• 5+ years in data science, ML engineering, or AI development
• Strong Python with solid software engineering practices
• Hands-on experience with Gen AI: LLMs, prompt engineering, RAG, embeddings, agents
• Deep analytical skills — ability to explore, understand, and interpret complex datasets to select the right approach (statistical, ML, or AI-based)
• Solid grounding in classical data science methods (statistical modeling, feature engineering, hypothesis testing) — knowing when not to use LLMs
• Production deployment of ML/AI systems (APIs, microservices, cloud — AWS/Azure/GCP)
• Familiarity with evaluation frameworks and model observability

Nice to Have

• Vector databases (Pinecone, Weaviate, FAISS)
• LLM fine-tuning or RLHF experience
• Databricks / large-scale data platforms
• Agentic frameworks (LangChain, LlamaIndex, AutoGen)
• Async/streaming architectures

Who You Are Curious and rigorous — you think in experiments but build for production. You bridge the gap between data science and engineering, and care about impact, quality, and reusable foundations.