Director, AI Engineering

Lantern

6h•Remote

About The Position

Lantern is looking for a Director of AI Engineering to lead the strategy, development, and delivery of AI and machine learning capabilities across the organization. This is a senior leadership role responsible for building and scaling a high-performing AI engineering team, setting the technical vision for ML/LLM systems, and ensuring that AI initiatives are tightly aligned with Lantern’s product strategy, care workflows, and business objectives. You will report to the VP of Engineering and work closely with executive leadership to shape how AI transforms care delivery and operations at Lantern. In this role, you will own the end-to-end AI engineering function—from research and prototyping through production deployment and continuous improvement. You will be expected to move fast, driving rapid proof-of-concept development and delivering production-grade AI solutions on aggressive timelines. You will establish the technical roadmap, define engineering standards, build team culture, and drive execution across multiple concurrent AI initiatives. Your work will directly impact how Lantern leverages intelligent systems to improve patient outcomes, operational efficiency, and scalable growth.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent experience; Master’s preferred.
10+ years of experience in software engineering or machine learning, with at least 4 years in a leadership role managing ML/AI teams.
Proven track record of building and shipping production ML/LLM systems at scale, including end-to-end ownership from research through deployment.
Deep technical expertise in ML frameworks (PyTorch, TensorFlow, scikit-learn), LLM technologies (prompt engineering, RAG, embeddings, fine-tuning, agents), and modern MLOps practices.
Strong experience with cloud-native ML infrastructure on Azure, including Azure ML, Databricks, and Azure DevOps pipelines.
Demonstrated ability to rapidly prototype AI solutions and drive them to production on aggressive timelines.
Experience with big data ecosystems (Spark, Databricks, Delta Lake) and streaming technologies.
Excellent leadership skills: hiring and developing high-performing teams, managing cross-functional relationships, and influencing at the executive level.
Strong strategic thinking with the ability to balance long-term vision with near-term execution and business impact.
Experience operating in regulated environments, ideally healthcare, with an understanding of compliance, data governance, and responsible AI principles.
Outstanding communication skills with the ability to translate complex technical concepts for non-technical stakeholders and executive audiences.

Nice To Haves

Experience applying AI/ML capabilities in healthcare, health tech, or other regulated industries.
Background working with clinical data, claims data, or healthcare operational workflows.
Experience building and scaling AI teams from the ground up, including defining team structure, processes, and culture.
Track record of delivering AI-powered products that drove measurable business outcomes.
Experience with LLM agents, agentic workflows, tool-use orchestration, or multi-step reasoning systems.

Responsibilities

Define and execute the AI engineering strategy and technical roadmap, ensuring alignment with Lantern’s product, clinical, and business priorities.
Build, lead, and scale a high-performing AI engineering team, including hiring, mentoring, performance management, and creating a culture of technical excellence and innovation.
Drive rapid AI proof-of-concept development, moving from problem identification to working prototypes on aggressive timelines, and shepherding successful POCs into production-grade systems.
Own the end-to-end lifecycle of ML/LLM systems—from research and experimentation through production deployment, monitoring, and continuous improvement.
Establish and maintain best-in-class MLOps practices: experiment tracking, reproducibility, CI/CD for models, automated testing, drift detection, observability, and scalable infrastructure on Azure.
Partner with product, clinical operations, marketing, data, and engineering leadership to identify high-impact AI opportunities and translate them into well-scoped, executable initiatives.
Lead architecture decisions for ML/LLM systems, ensuring scalability, reliability, security, and compliance with healthcare regulations.
Establish clear KPIs and success metrics for the AI engineering function, including model performance, delivery velocity, team health, and business impact.
Champion responsible AI practices across the organization, including fairness, transparency, explainability, and regulatory compliance in healthcare contexts.
Represent the AI engineering function to executive leadership, providing regular updates on progress, risks, and strategic recommendations.
Build external visibility for Lantern’s AI capabilities through thought leadership, community engagement, and talent brand building.