AI Engineer — Applied AI

About Our Client

The organization operates in the healthcare and life sciences sector, addressing the challenge of extracting value from unstructured medical data. It develops a platform that integrates advanced large language models (LLMs) with domain-specific quality controls to transform free-text clinical records into structured, analysis-ready data efficiently and accurately. Serving leading institutions in healthcare, life sciences, and research, the organization supports faster studies, improved insights, and enhanced patient care. It is backed by a publicly traded parent company and focuses on positioning structured data as a foundation for innovation.

About the Opportunity

The AI Engineer is responsible for enhancing the quality and efficiency of the clinical data platform. This applied-AI role requires versatility across software engineering, data science, experimentation, and production operations. The position focuses on analyzing the effects of pipeline changes on system performance and implementing improvements across model interactions, information retrieval, workflow control, and output validation. The role contributes to making AI systems measurably better and turning experiments into real product capabilities.

Responsibilities

• Develop software programming paradigms for platform interactions with LLMs under different token usage scenarios
• Build evaluation frameworks to assess cost-performance trade-offs of various language models relevant to core workloads
• Collaborate with clinical experts to encode domain knowledge and establish quality standards
• Create test suites measuring accuracy, completeness, consistency, latency, and cost
• Design controlled experiments to assess effects of platform changes
• Enhance model interactions through prompting, structured outputs, tool integration, context management, and workflow design
• Develop datasets and internal tools for evaluation, regression testing, and rapid iteration

Requirements

• Minimum 5 years of experience in applied machine learning, AI engineering, data science, or related software engineering roles
• Proficiency in Python and SQL
• Practical experience developing production applications using LLMs
• Ability to design experiments and interpret complex, noisy results
• Familiarity with LLM evaluation, retrieval-augmented generation, agentic workflows, or MLOps
• Strong software engineering skills with capability to deliver reliable production code
• Intellectual curiosity, sound judgment, and refined technical taste

Pay and Compensation

• Expected base salary generally between $175,000 and $250,000 per year, with meaningful equity
• Final compensation varies based on experience, expertise, business needs, and market conditions
• Compensation may include discretionary bonuses and company-sponsored benefit programs
• Position is at-will and salary may be modified based on performance and business factors