AI Engineer
Skills
AdoptionConnectorsDecision SupportEnhanced Data Rates For GSM EvolutionFairness OpinionsHealthcareInterest Rates
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 3+ years of professional experience in data engineering backend engineering machine learning or a related field
- 1+ years of hands-on experience building with LLM APIs and agentic orchestration frameworks
- Strong Python and SQL proficiency
- Experience with cloud data platforms such as AWS and Databricks
- Solid understanding of data modeling ETL ELT patterns and medallion architecture
- Experience building and consuming APIs
- Demonstrated experience with prompt engineering agent evaluation and validating LLM outputs
- Experience designing evaluation frameworks test cases and QA for AI ML systems
- Ability to measure AI system performance using accuracy precision recall and hallucination rates
- Strong debugging and analytical skills in ambiguous technical territory
- Excellent written and verbal communication skills
- Comfortable working in a fast-moving environment with incomplete information
Nice to have
- Cross-functional
- Healthcare domain
- Startup experience
- Regulated domain
Day to day
- Design, build, and maintain agentic systems and LLM-powered applications that automate complex healthcare workflows.
- Orchestrate multi-step agents that retrieve data infer clinical logic and use tools to solve high-stakes problems.
- Collaborate with engineering product and clinical teams to deliver validated production-grade AI solutions with strong guardrails.