Senior Large Language Model (LLM) Operations Engineer

N-Power Medicine is focused on transforming clinical trials through innovative AI solutions. The Senior LLM Operations Engineer will lead the technical strategy for scaling AI innovation in clinical variable abstraction and note generation, ensuring robust and automated deployment of machine learning solutions. Responsibilities: Architect and spearhead the development of cutting-edge, scalable AI infrastructure, including novel human-in-the-loop (HITL) paradigms, ensuring our systems learn effectively from feedback; Lead the technical design and implementation of core MLOps components and systems for our LLMs—including CI/CD, monitoring, and automated feedback loops—ensuring robustness, scalability, and adherence to software engineering best practices; Define and shape solutions for complex automation and deployment challenges, enabling the strategic application of our cutting-edge AI; Drive technical alignment and integration with AI Data Science and Software Engineering teams, ensuring the seamless transition of AI solutions from research into production environments and influencing architectural standards; Define and establish standards for the rigorous validation, monitoring, and lifecycle management of AI products, ensuring continuous accuracy improvement and reliability in production; Define, champion, and drive adoption of best practices for MLOps, including model/data versioning, experiment tracking, and reproducibility within the AI/ML domain; actively mentor others; Identify, champion, and integrate state-of-the-art MLOps technologies and frameworks, driving innovation and maintaining our technical edge in AI deployment; Provide expert guidance on applying safeguards and protections (HIPAA, privacy laws) to our model deployment and data handling pipelines; champion and uphold the highest compliance, quality, and security standards Qualifications: 3+ years of professional experience in an MLOps, DevOps, or Software Engineering role with a focus on machine learning systems; MSc/BSc graduate in engineering, computer science, or a relevant field, with extensive equivalent experience. A PhD is a plus; Deep, hands-on expertise in Python and proficiency in modern software development practices; Hands-on experience with a major cloud platform (AWS, GCP, or Azure); Strong experience with containerization and orchestration technologies (Docker, Kubernetes); Proven experience building and maintaining CI/CD pipelines for complex applications (e.g., GitHub Actions, Jenkins), particularly those that include data + model versioning; A proven track record of technical leadership and high-impact contributions in building and scaling production machine learning systems; Proven ability to independently define, architect, and lead solutions for complex, ambiguous infrastructure problems, clearly articulating business value; Demonstrated ability to lead the decomposition of large-scale systems and guide teams in delivering incremental solutions; Track record of designing sustainable, reusable, and high-quality code and influencing team/organizational standards; Exceptional written, verbal, and presentation skills; ability to influence stakeholders at all levels; Recognized technical leader, proactive, strategic thinker, and takes end-to-end ownership; Generous, Curious, and Humble Required Skills: MLOps, Python, AWS, GCP, Azure, Docker, Kubernetes, CI/CD, GitHub Actions, Jenkins, Data Versioning, Machine Learning Systems, Communication, Strategic Thinking