Senior Applied AI/ML Engineer
Skills
AdoptionContinuous ImprovementDatabasesFairness OpinionsHealthcareLarge Language ModelsOptimization
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5–8+ years building production software systems
- Experience building and operating applied AI ML LLM-powered or agentic systems in production
- Strong software engineering background with Python and backend systems for production-scale AI applications
- Experience designing and interpreting experiments evaluation frameworks benchmarks or performance measurement systems
- Proven ability to translate complex operational requirements and real-world data into reliable scalable shipped products
- Understanding of production engineering practices including testing monitoring observability reliability and safe rollouts
- Product-oriented mindset with ability to navigate ambiguity make thoughtful technical decisions and drive initiatives from concept through deployment
- Strong communication and collaboration skills across engineering product data and operational teams
Nice to have
- Product-oriented
- Ambiguous environment
- Low-ego
- Fast-moving
Day to day
- Design, build, deploy, and improve production AI systems that power healthcare reimbursement workflows
- Develop LLM-based applications using retrieval, structured generation, tool use, orchestration, and agentic workflows
- Partner with product, operations, data, and engineering teams to translate complex business problems into scalable AI solutions and measure outcomes