Staff Software Engineer, AI & Recommendations Platform

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. 

Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about and hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals.

About the Role:

How can we use vast amounts of proprietary and internet-scale healthcare data to build systems that enable access to significantly better healthcare?

As a Staff Software Engineer on the AI team, you will play a key technical leadership role in evolving AI & Recommendations platform. You will help build the systems, infrastructure, and services that power treatment recommendations, provider decision support and experimentation across multiple healthcare verticals.

This role is ideal for an engineer who is passionate about building scalable platforms and production systems while leveraging machine learning and AI technologies to solve complex healthcare problems. You will work across the stack—from APIs and platform infrastructure to recommendation systems and LLM-powered applications—to enable intelligent, personalized care at scale.

You Will:

• Lead the design and development of scalable backend systems, APIs, and platform services that power treatment recommendations and personalization.

• Architect and build the infrastructure that enables experimentation, recommendation engines, and AI-powered healthcare experiences

• Partner with Machine Learning engineers to productionize models and integrate intelligent decisioning into customer and provider workflows

• Design and implement highly reliable, observable, and maintainable distributed systems

• Drive platform investments including self-service tooling, testing infrastructure, unified decisioning frameworks, and data pipelines

• Collaborate with vertical engineering teams to establish reusable patterns, frameworks, and best practices that enable independent innovation

• Evaluate and integrate emerging AI and LLM technologies where they can improve provider efficiency, patient outcomes, or operational scale

• Lead complex technical initiatives that span multiple teams and systems

• Mentor engineers and provide technical leadership through design reviews, architecture discussions, and hands-on implementation

• Influence the long-term technical direction of the MedMatch platform and broader AI ecosystem

You Have:

• 5+ years of professional software engineering experience building and operating production systems at scale

• Strong expertise in backend engineering, distributed systems, APIs, and cloud-native architectures

• Demonstrated success leading large technical initiatives and influencing architecture across teams

• Experience building data-intensive applications and services that leverage machine learning or recommendation systems

• Strong proficiency in Python and modern software development practices

• Experience integrating ML models, recommendation engines, or LLM-powered applications into production systems

• Familiarity with ML lifecycle concepts including training, evaluation, deployment, monitoring, and experimentation

• Experience with cloud platforms and modern infrastructure tooling (AWS, Kubernetes, Databricks, MLflow, Airflow, etc.) is a plus

• Ability to balance short-term product delivery with long-term platform scalability and maintainability

• Excellent collaboration and communication skills, with the ability to work effectively across engineering, product, data science, and clinical stakeholders

Nice to Have:

• Experience building recommendation systems, ranking systems, personalization platforms, or decision-support systems

• Experience in he