AI Engineer Data Science & Generative AI

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 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.