Senior AI Engineer
Skills
ContextDatabasesElasticsearchEnhanced Data Rates For GSM EvolutionHealthcareInterest RatesLarge Language Models
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Strong hands-on experience building production AI applications using LLMs RAG agents or related architectures
- Experience shipping and maintaining production-grade AI systems not just prototypes
- Strong software engineering skills in Python Node.js or similar languages
- Experience with large-scale data processing ingestion pipelines ETL ELT or workflow orchestration
- Experience with vector databases embeddings search indexing retrieval and ranking systems
- Understanding of prompt design structured outputs tool calling and multi-step AI workflows
- Ability to work with messy real-world data and design robust scalable pipelines
- Experience working in a startup early-stage company or similarly fast-moving environment
- Ability to take ownership of problems end-to-end from architecture and implementation through deployment monitoring and iteration
Nice to have
- High ownership
- First principles thinker
- Product focused
- Ambiguity tolerant
- Fast learner
- Detail oriented
Day to day
- Build production AI systems for clinical research and patient matching using LLMs RAG and agentic workflows
- Design and improve data pipelines over structured and unstructured healthcare sources including EHR data FHIR resources PDFs clinical notes and trial criteria
- Develop retrieval ranking and evaluation systems that improve accuracy reliability latency and cost in real-world deployments
Hiring process
- Share your CV
- Include GitHub or portfolio if available
- Provide a short note on one production AI system or data pipeline you are proud of