Manager, AI Engineering

Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building.

Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare's greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.

You are a hands-on technical leader who turns AI strategy into reliable, compliant products that create measurable value for healthcare organizations. As Manager, AI Engineering, you lead and develop an established team while staying close to the technology to guide architecture, review technical decisions, and help solve complex engineering problems. You sit within the AI organization, report to the Director of AI, and partner closely with Product, Security, Legal, Compliance, and executive stakeholders to deliver production AI systems at scale.

• Lead, coach, and develop an existing team of 5+ engineers through clear expectations, regular one-on-ones, structured feedback, and support for hiring and onboarding.
• Own end-to-end engineering execution, including planning, prioritization, delivery quality, team health, and production incident response.
• Translate the AI roadmap into quarterly plans with measurable outcomes and report progress, risks, and impact metrics to leadership.
• Partner with AI Product Managers to shape the roadmap, scope use cases, and determine where AI creates the most value.
• Guide the architecture of production AI solutions using classical machine learning, generative AI, LLMs, RAG, OCR and document AI, and agentic workflows.
• Make sound technical trade-offs across accuracy, latency, cost, reliability, safety, and scalability, including choosing between classical ML and generative approaches.
• Review designs, code, and experiments, and stay hands-on with prototypes and proofs of concept to unblock the most difficult problems.
• Build reusable components, reference architectures, and internal platforms that turn one-off solutions into scalable capabilities.
• Ensure AI systems comply with Inovalon security standards and applicable regulations by partnering with Security, Legal, and Compliance on auditability, readiness, and risk reviews.
• Build human-in-the-loop review, explainability, and bias monitoring into AI systems where clinical or financial decisions may be affected.

• 10+ years of total experience in software engineering, machine learning, or data science, with 3-5 years of people management experience leading teams of 3-5 engineers or data scientists.
• Bachelor's or Master's degree in Computer Science, AI, Data Science, Statistics, or a related field, or equivalent combination of education and experience required.
• Proven experience delivering both classical ML and LLM-based or agentic applications into production, and owning the technical architecture of AI systems end to end.
• Experience working with sensitive or regulated data, with healthcare strongly preferred.
• Strong expertise in end-to-end AI solution design, classical ML, LLMs and document AI, agentic AI, RAG pipelines, vector databases, Python, SQL, CI/CD, Docker, Kubernetes, AWS, MLflow, observability tools, and data pipelines using Spark or Airflow.
• Experience coaching, mentoring, performance management, hiring, Agile/Scrum delivery, and communicating complex AI concepts to product, clinical, compliance, and executive stakeholders.
• Demonstrate Growth Potential & Learning Agility by quickly learning new AI methods, tools, and healthcare use cases and applying that learning to improve team performance and product outcomes.
• Demonstrate Leadership by developing engineers, influencing cross-functional partners, building strong relationships across distributed teams, and balancing hands-on technical work with management responsibilities.
• Demonstrate Adaptability by adjusting priorities, delivery plans, and technical approaches in response to ambiguity, changing business needs, and evolving product requirements.
• Demonstrate Creative Thinking by designing practical, innovative AI solutions that solve real business problems and create…