Lead AI Engineer

Overview

We are looking for a hands-on and visionary Lead AI Engineer to drive the development, deployment, and scaling of AI capabilities across our platform. In this role, you will lead a small but growing team of AI engineers, shaping the roadmap, setting best practices, and ensuring the delivery of production-grade, high-impact AI solutions. You will serve as a bridge between technical implementation and business value, working closely with engineering leadership, product teams, and domain experts.

This role requires a deep understanding of AI/ML systems, strong architectural instincts, and a passion for mentoring and growing talent. You will help us navigate the evolving AI landscape and translate promising opportunities into scalable, real-world solutions that improve patient outcomes and drive our mission forward.

Specifics

The responsibilities for this role include, but are not limited to:

AI Strategy & Technical Leadership

· Define and refine our AI engineering strategy in alignment with business goals and product opportunities.

· Design and guide the implementation of end-to-end AI/ML pipelines, including data ingestion, model training, deployment, and monitoring.

· Stay current with industry trends in AI/ML and evaluate their potential for application in our healthcare platform.

Team Leadership & Mentorship

· Lead, mentor, and support a team of AI engineers, including direct supervision of junior AI engineers.

· Establish engineering best practices for AI development, including coding standards, peer reviews, and model governance.

· Foster a collaborative, feedback-driven team culture rooted in our company values: integrity, grit, collaboration, and adaptability.

Cross-functional Collaboration

· Work closely with product management, data engineering, domain experts, and software engineers to define problem statements and deliver AI-powered features.

· Translate business needs into actionable technical approaches that consider data availability, ethical implications, and operational constraints.

· Communicate clearly with both technical and non-technical stakeholders to ensure alignment and transparency.

Productionization & MLOps

· Own the architecture and scalability of deployed AI models in cloud environments.

· Implement monitoring and retraining workflows to ensure long-term reliability and performance of AI solutions.

· Contribute to infrastructure decisions related to model training environments, deployment tools, and experimentation platforms.

Requirements

Education

· Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. PhD is a plus.

Experience

·6+ years of experience working in AI/ML roles, with 2+ years of experience in a technical leadership position.

· Proven track record of developing and deploying machine learning systems into production environments.

· Experience leading cross-functional efforts and mentoring junior engineers.

Technical Skills

· Advanced proficiency in Python and core machine learning libraries (TensorFlow, PyTorch, Scikit-learn, etc.).

· Deep understanding of applied ML techniques including NLP, classification, prediction, and time-series analysis.

· Hands-on experience working with Generative AI models (e.g. GPT, LLaMA, Claude), including prompt engineering, fine-tuning, and integrating GenAI into production applications.

· Strong grasp of MLOps principles and tools for model lifecycle management (e.g., MLflow, SageMaker, Vertex AI).

· Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

· Solid grounding in algorithms, data structures, and applied mathematics .

Soft Skills

· Demonstrated ability to communicate technical concepts clearly across audiences.

· Strong sense of ownership and accountability in both individual and team contributions.

· Passion for growing talent and building an inclusive, learning-focused team culture.

Preferred

· Experience with healthcare, real-world data (e.g., claims, EMR), or regulated environments (e.g., HIPAA compliance).

· Familiarity with responsible AI practices, model explainability, and ethical considerations in AI design.

· Experience integrating AI features into large-scale, distributed systems.

What We Offer

· Opportunity to lead AI efforts in a mission-driven, healthcare-focused technology company.

· A collaborative, expert-driven team environment focused on impact, not ego.

· A role where you can influence both strategic direction and technical implementation.

· Access to modern cloud infrastructure and the autonomy to shape AI systems that matter.