Senior Large Language Model (LLM) Operations Engineer

N-Power Medicine is a company focused on transforming clinical trials and drug development through innovative AI solutions. They are seeking a Senior LLM Operations Engineer to architect and manage scalable AI infrastructure and MLOps systems, ensuring the effective 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

Requirements:

• 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
• Direct experience productionizing Large Language Models (LLMs), including knowledge of prompting strategies, RAG, and fine-tuning
• Deep expertise with the Databricks platform, including MLflow, Delta Tables, and Unity Catalog
• Experience building data annotation and Human-in-the-Loop (HITL) systems from the ground up
• Familiarity with vector databases (e.g., Pinecone, Chroma) and model serving frameworks (e.g., Ray Serve, Triton, and Databricks/Mosaic)
• Experience working in a regulated environment, particularly with healthcare data (HIPAA)