About Bobsled

Bobsled 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 Do

• Own the text-to-SQL accuracy problem end-to-end: design evals, iterate prompts, and improve retrieval/routing

• Build 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 latency

• Ship production-grade code and support deployments; instrument, monitor, and troubleshoot model behavior in real customer environments

• Partner closely with engineering and customers to improve semantic models, SQL generation, and data alignment

• Create feedback loops from users to systematically capture issues and convert them into measurable improvements

• Contribute to automation of environment provisioning and dev workflows to enable fast iteration

What We’re Looking For

• 2+ years in ML/AI or data-focused engineering or data science roles building production systems data or AI systems

• Demonstrated experience tuning LLM applications: prompt engineering, evals, retrieval, agent design, or similar

• Strong 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 production

• Comfort with SQL and complex data modeling; familiarity with data warehouses and pipelines

• Pragmatic, product-oriented approach—optimize for impact over novelty; complement existing systems rather than rebuild from scratch

• Ability to design experiments, quantify improvements, and communicate trade-offs clearly

Nice to Have

• Experience with text-to-SQL systems, semantic layers, or BI/analytics workflows

• Exposure to RAG frameworks, knowledge graphs, vector stores, and evaluation tooling

• Prior work in analytics engineering or data engineering environments

Success Looks Like

• Measurable improvements in text-to-SQL accuracy across target datasets and partners

• Reliable eval pipeline and regression suite running in CI to catch degradations

• Clear architecture and documentation for context/agent systems that others can contribute to

• Short feedback cycles with partners leading to fast, meaningful product wins

Compensation & Benefits

• Competitive Salary and Equity

• Health Insurance: Medical (100% paid), dental, and vision benefits for you and your family

• Generous PTO policy and paid parental leave

• Fully upgraded Apple MacBook and 4K monitor (for engineering team only)

• Home office stipend of $1,000

• Flexible work hours in a fully remote work environment

• Fully sponsored individual coaching for all employees to help foster a culture of personal reflection and growth (optional but encouraged)

  #LI-REMOTE