Job description

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFR CT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFR CT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare. Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 750,000 patients worldwide. About the role To accelerate this mission, we are seeking an Engineering Manager to build and lead our new Agentic AI initiatives team. This is a unique "player-coach" opportunity. You will start in a deeply hands-on capacity - acting as the lead architect and foundational engineer to set up the core ecosystem that allows autonomous, intelligent agents to execute multi-step medical reasoning securely and at scale. As the foundation is laid and the product gains momentum, your role will transition into a full Engineering Manager capacity. You will be responsible for scaling a world-class team of engineers, guiding their execution, and shaping the long-term technical strategy of the platform. You will have a true blank-canvas opportunity to design production-grade agentic systems from scratch, directly translating our decade-plus of clinical AI success into the next generation of autonomous medical technology. Job Responsibilities Initial Hands-On Execution: Design, architect, and write code for a robust, secure, and scalable Agentic AI platform, establishing standard patterns for multi-agent orchestration, state management, tool usage, and memory. Team Building & Leadership: Transition from an individual contributor/architect role into a dedicated management role as the team scales. Technical Strategy: Drive the technical execution of brand-new, agent-driven product features from initial ideation to production deployment. Build systems to parse requirements, map software modules, and auto-generate test cases. Safety & Compliance: Implement advanced guardrails, evaluation frameworks, and reasoning validation loops to ensure agent behaviors are safe, deterministic, highly accurate, and meet the compliance rigor required for FDA-cleared software. Cross-Functional Collaboration: Work closely with product managers, clinical experts, and data scientists to translate clinical needs into technical AI agent architectures and viable product roadmaps. Best Practices: Champion software engineering best practices (CI/CD, comprehensive testing, logging for non-deterministic systems) and keep the team ahead of the rapidly evolving AI landscape. Required Qualifications 8+ years of professional software engineering experience, with a proven track record of shipping production-grade software. 5+ years of experience managing, mentoring, or acting as a formal technical lead for software engineering teams. Player-Coach Mentality: Willingness and technical capability to be deeply hands-on with code and architecture during the first 6–12 months while concurrently building the team. Deep, hands-on experience building applications with Large Language Models (LLMs) and a strong understanding of agentic architectures, orchestration frameworks, and vector databases. Advanced proficiency in Python or Go, alongside a solid grasp of microservices, API design, and cloud infrastructure (AWS or GCP). A passion for greenfield projects - you thrive in ambiguity, enjoy designing systems from scratch, and love solving complex, open-ended problems. Nice-to-Have Experience deploying AI applications in regulated industries (Healthcare, Finance, etc.) or navigating HIPAA/GDPR compliance. Active contributions to open-source LLM or Agentic AI frameworks. Experience with advanced prompt engineering, fine-tuning, or RAG optimization. A reasonable estimate of the base salary compensation range is $200,000 to $270,000, cash bonus, and equity. #LI-IB1 #LI-Hybrid Heartflow is an Equal Opportunity Employer. We are committed to a work environment that supports, inspires, and respects all individuals and do not discriminate against any employee or applicant because of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law. This policy applies to every aspect of employment at Heartflow, including recruitment, hiring, training, relocation, promotion, and termination. Positions posted for Heartflow are not intended for or open to third party recruiters / agencies. Submission of any unsolicited resumes for these positions will be considered to be free referrals. Heartflow has become aware of a fraud where unknown entities are posing as Heartflow recruiters in an attempt to obtain personal information from individuals as part of our application or job offer process. Before providing any personal information to outside parties, please verify the following: A) all legitimate Heartflow recruiter email addresses end with “@heartflow.com” and B) the position described is found on our careers site at www.heartflow.com/about/careers/ .

Requirements

Must-haves

To accelerate this mission, we are seeking an Engineering Manager to build and lead our new Agentic AI initiatives team.
Team Building & Leadership: Transition from an individual contributor/architect role into a dedicated management role as the team scales.
Cross-Functional Collaboration: Work closely with product managers, clinical experts, and data scientists to translate clinical needs into technical AI agent architectures and viable product roadmaps.
Best Practices: Champion software engineering best practices (CI/CD, comprehensive testing, logging for non-deterministic systems) and keep the team ahead of the rapidly evolving AI landscape.
8+ years of professional software engineering experience, with a proven track record of shipping production-grade software.
5+ years of experience managing, mentoring, or acting as a formal technical lead for software engineering teams.
Player-Coach Mentality: Willingness and technical capability to be deeply hands-on with code and architecture during the first 6–12 months while concurrently building the team.
Deep, hands-on experience building applications with Large Language Models (LLMs) and a strong understanding of agentic architectures, orchestration frameworks, and vector databases.
Advanced proficiency in Python or Go, alongside a solid grasp of microservices, API design, and cloud infrastructure (AWS or GCP).
A passion for greenfield projects - you thrive in ambiguity, enjoy designing systems from scratch, and love solving complex, open-ended problems.

Nice-to-haves

Experience deploying AI applications in regulated industries (Healthcare, Finance, etc.) or navigating HIPAA/GDPR compliance.
Active contributions to open-source LLM or Agentic AI frameworks.
Experience with advanced prompt engineering, fine-tuning, or RAG optimization.
Positions posted for Heartflow are not intended for or open to third party recruiters / agencies. Submission of any unsolicited resumes for these positions will be considered to be free referrals.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdpythongoapiawsgcpllm

Platform: greenhouse
Effort: quick