## About the RoleJoin us in redefining how legal teams work by building state-of-the-art AI-native experiences powered by Large Language Models. As an AI Engineer, you’ll work across backend systems, evaluation frameworks, and agentic LLM workflows to create scalable, secure, and continuously improving AI features. You’ll partner closely with design, product, and legal teams to bring thoughtful, high-impact functionality to life.## Qualifications4+ years building user-facing software (B2B SaaS is a plus). Strong Python skills and comfort with at least one other backend language. Production experience building with LLMs or similar AI services. Solid understanding of APIs, cloud infrastructure, and scalable backend design. Proven loop for improving model quality: - Building/maintaining eval datasets and regression suites. - Running offline evals and online experiments, interpreting results. - Observability for LLM systems (traces, latency/cost tracking, drift detection). Product sense and curiosity—you think in terms of user outcomes, not just code paths.## ResponsibilitiesBuild and integrate LLM-powered features in production. Define success metrics (task success, grounding, latency, cost) and set practical SLOs. Create and maintain evaluation datasets: golden sets, adversarial cases, and regression suites. Automate quality checks with an offline eval harness, CI gates, and safe online tests (A/B, canaries). Instrument tracing and logs for prompts, responses, errors, and costs; analyze failures and ship fixes. Improve quality end-to-end: prompt design, retrieval (RAG), model selection/fine-tuning, and post-processing. Work across APIs, data pipelines, and backend services to deliver complete user workflows. Collaborate with product and design so the AI feels helpful and trustworthy. Keep privacy, reliability, and performance front and center. #J-18808-Ljbffr