AI/ML Engineer, Applied Data Science

The AI/ML Engineer builds AI capabilities from prototype to production. You will develop prompt engineering solutions, RAG pipelines, AI agents, and evaluation frameworks — starting with rapid prototypes to validate use cases, then engineering them into scalable, production-grade systems. This role requires both the creativity to explore what's possible and the rigor to build what's reliable. Minimum Qualifications 4+ years of delivering solutions in AI/ML engineering, NLP, or related roles Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar) Experience with LLM APIs (OpenAI, Anthropic, or similar) Experience with RAG architectures and vector databases Understanding of prompt engineering techniques and best practices Experience taking AI systems from prototype to production Experience with evaluation frameworks for AI systems Supporting AI applications in production Preferred Qualifications Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks Experience with agentic AI frameworks (LangGraph, CrewAI, or similar) Familiarity with knowledge graphs and GraphRAG patterns Experience with AI evaluation tools (RAGAS, DeepEval, or similar) Knowledge of legal domain and legal NLP applications Experience with guardrails and safety frameworks (Guardrails AI, NeMo Guardrails) Understanding of MCP (Model Context Protocol) or similar integration patterns Experience deploying and monitoring AI systems at scale Track record of shipping AI products that users rely on