Company Name: Bobsled

Job Details: Be,an,Early,Applicant,Hiring,Remotely,in,US,Remote,Junior

Job Url: https://builtin.com/job/ai-engineer/7738766

Job Description: About BobsledBobsled is building AI-powered analytics experiences that turn natural language into accurate, production-grade insights. We’re looking for a hands-on AI Engineer to drive text-to-SQL accuracy and the systems that make our LLM-based application reliable in production.What You’ll DoOwn the text-to-SQL accuracy problem end-to-end: design evals, iterate prompts, and improve retrieval/routingBuild and operate the experimentation and evaluation loop (automatic evals, regression suites, dataset curation)Design pragmatic LLM application architectures (RAG, agent routing, tool-use orchestration) optimized for accuracy and latencyShip production-grade code and support deployments; instrument, monitor, and troubleshoot model behavior in real customer environmentsPartner closely with engineering and customers to improve semantic models, SQL generation, and data alignmentCreate feedback loops from users to systematically capture issues and convert them into measurable improvementsContribute to automation of environment provisioning and dev workflows to enable fast iterationWhat We’re Looking For2+ years in ML/AI or data-focused engineering or data science roles building production systems data or AI systemsDemonstrated experience tuning LLM applications: prompt engineering, evals, retrieval, agent design, or similarStrong hands-on coding in Python or TypeScript (TypeScript familiarity a plus; willingness to work across the stack required)ML engineering mindset beyond notebooks: testing, CI, observability, performance, and deployment in productionComfort with SQL and complex data modeling; familiarity with data warehouses and pipelinesPragmatic, product-oriented approach—optimize for impact over novelty; complement existing systems rather than rebuild from scratchAbility to design experiments, quantify improvements, and communicate trade-offs clearlyNice to HaveExperience with text-to-SQL systems, semantic layers, or BI/analytics workflowsExposure to RAG frameworks, knowledge graphs, vector stores, and evaluation toolingPrior work in analytics engineering or data engineering environmentsSuccess Looks LikeMeasurable improvements in text-to-SQL accuracy across target datasets and partnersReliable eval pipeline and regression suite running in CI to catch degradationsClear architecture and documentation for context/agent systems that others can contribute toShort feedback cycles with partners leading to fast, meaningful product winsCompensationCompetitive salary and meaningful equityComprehensive benefits #LI-REMOTE-Remote