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Engineering Manager, Data

About Rad AI

At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding, including a recently oversubscribed $60M Series C round led by Transformation Capital, bringing our valuation to $525M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact.

If you’re ready to shape the future of healthcare, we’d love to have you on our team!

Why Join Us:

This role will lead our Data Engineering team to support our rapid client growth and projected expansion in the year ahead. In this role, you will play an instrumental part in the construction and maintenance of data collection systems, pipelines, and management tools, as well as managing the data engineering team. As the authority over the construction and continued operation of Rad AI data systems.

What You’ll Be Doing:

  • Report into our Director of Engineering to manage a team of software engineers at a variety of levels.

  • Cross-functionally partner with other groups, including platform engineering, machine learning, product management to advance product features.

  • Bring clarity to ambiguous situations, ensuring feature development aligns with long-term KPI improvements.

  • Invest in individual growth, enabling your team to deliver with quality and confidence.

  • Collaborate with senior leadership to chart out a strategic direction based on vital business metrics.

  • Prioritize clear, constructive feedback, ensuring everyone on the team is aligned and empowered.

Who We’re Looking For:

  • 7+ years of engineering experience with a minimum of 2+ years of engineering management experience.

  • Experience leading cross-functional product engineering teams focused on shipping with quality.

  • Ability to understand KPI and business metrics, as well as the ability to identify and scope product feature work to maximize the business impact.

  • Previous experience in performance management, including the ability to mentor and guide the professional and technical development of your team members.

  • A bias to take action, and an ability to use best available data to justify your actions and opinions and make decisions that move the business forward.

  • Expertise in growing teams, and previous experience recruiting engineers of multiple disciplines while ensuring a successful, supportive onboarding experience.

  • Ability to plan ahead for potential obstacles, communicate areas of risk, and provide clear directives. Anticipate potential obstacles and plan accordingly.

  • Have a philosophy of valuing each team member and understanding individual strengths and areas for growth.

  • Ability to be hands on if needed.

  • Demonstrated familiarity with data engineering best practices and tools (e.g., Airflow, dbt, Kafka, or Spark) to help oversee data pipelines and data transformation work.

  • Experience working with cloud-based data warehouses or data lakes (e.g., AWS Redshift, Snowflake, BigQuery) and an understanding of data modeling and ETL/ELT processes.

  • Comfortable with DevOps practices and infrastructure-as-code (e.g., Terraform, CloudFormation) to support reliable data infrastructure.

Nice to Haves:

  • Experience in a healthcare startup or radiology-focused organization.

  • Familiarity with healthcare data standards (e.g., HL7, FHIR) and relevant privacy/security regulations (HIPAA, HITRUST).

Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission,  we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!

Rad AI offers a variety of benefits, including:

  • Comprehensive Medical, Dental, Vision & Life insurance

  • HSA (with employer match), FSA, & DCFSA 

  • 401(k)

  • 11 Paid Company Holidays

  • Location Flexibility (Remote-first company!)

  • Flexible PTO policy

  • Annual company-wide offsite

  • Periodic team offsites

  • Annual equipment stipend

At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com or no-reply@ashbyhq.com.

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CEO of Rad AI
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Average salary estimate

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$130000K
$160000K

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What You Should Know About Engineering Manager, Data, Rad AI

At Rad AI, we believe that healthcare can be transformed through the power of artificial intelligence, and as an Engineering Manager, Data, you'll be at the forefront of this exciting mission! With over 7 years of engineering experience, including 2 years in a management role, you’ll lead a talented team of software engineers in developing and maintaining cutting-edge data systems that support our rapid growth. Imagine being responsible for overseeing data collection pipelines and management tools that enhance patient care across numerous healthcare systems. Collaborating with cross-functional teams, including platform engineering and product management, you'll drive development efforts aligned with our long-term goals. Your ability to guide and mentor your team members will be crucial, allowing them to shine and deliver high-quality outputs with confidence. If you're ready to take action and leverage data to make informed decisions, then this is the role for you. Join us in shaping the future of healthcare at Rad AI, where our world-class team works tirelessly to empower physicians and revolutionize patient care, while enjoying flexible, remote-first work arrangements and a variety of excellent benefits!

Frequently Asked Questions (FAQs) for Engineering Manager, Data Role at Rad AI
What are the key responsibilities of the Engineering Manager, Data at Rad AI?

As the Engineering Manager, Data at Rad AI, your key responsibilities include managing a diverse team of software engineers, overseeing data collection systems and pipelines, and collaborating cross-functionally with teams in platform engineering and product management. You will ensure feature development aligns with strategic business objectives while mentoring team members for professional growth.

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What qualifications are required for the Engineering Manager, Data position at Rad AI?

To excel in the Engineering Manager, Data position at Rad AI, candidates should have over 7 years of engineering experience, including at least 2 years in an engineering management role. Familiarity with data engineering practices, cloud-based data warehouses, and experience in leading cross-functional teams are also essential qualifications for the role.

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How does the Engineering Manager, Data role support Rad AI's mission?

The Engineering Manager, Data plays a pivotal role in supporting Rad AI's mission by overseeing the development of data systems that enhance the efficiency of clinical workflows and improve patient outcomes. By leveraging data engineering best practices, the manager ensures that the team delivers impactful solutions that empower physicians.

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What growth opportunities are available for the Engineering Manager, Data at Rad AI?

At Rad AI, as an Engineering Manager, Data, you will have abundant opportunities for professional growth. You will mentor engineers, collaborate with senior leadership to drive strategic direction, and be involved in recruiting future team members, enhancing your leadership skills and contributing to the company's expansion.

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What benefits can employees expect when joining Rad AI in the Engineering Manager, Data position?

When you join Rad AI as an Engineering Manager, Data, you can expect a comprehensive benefits package that includes medical, dental, and vision insurance, a flexible PTO policy, 401(k) with employer match, and the opportunity for remote work. Additionally, employees enjoy team-building off-sites and stipends for annual equipment.

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Common Interview Questions for Engineering Manager, Data
Can you describe your experience managing engineering teams?

When responding, highlight your previous management experiences, discussing specific teams you’ve led, projects you completed, and how you supported your team’s growth. Emphasize your leadership style and any metrics that demonstrate your impact, such as improved team performance or successful project deliveries.

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How do you prioritize projects and tasks for your team?

Explain your approach to project prioritization, including how you assess the urgency, impact, and alignment with business goals. Providing an example of how you set priorities based on company objectives can effectively demonstrate your analytical skills and organizational ability.

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What data engineering practices do you consider most critical?

Discuss key data engineering practices such as data pipeline design, ETL processes, and data modeling. Mention specific tools like Airflow or dbt that you’ve successfully implemented and how they contributed to the efficiency and reliability of past projects.

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How do you manage conflicts within your team?

Describe your conflict resolution strategy, emphasizing open communication, understanding individual perspectives, and creating a collaborative environment. Provide an example where you successfully resolved a conflict to illustrate your practical approach.

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What role does data play in decision-making in your engineering process?

Explain the importance of data in driving decision-making, highlighting how you utilize metrics and key performance indicators (KPIs) to inform product development and engineering practices. Providing a specific instance where data-led decisions positively impacted outcomes can strengthen your response.

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Can you give an example of a challenge you faced and how you overcame it?

When answering this question, focus on a significant engineering challenge you faced, the reasoning behind your approach to solving it, and the outcome. This showcases your problem-solving abilities and resilience in the face of difficult situations.

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How do you ensure the professional development of your team members?

Discuss your philosophy on professional development, including how you create growth opportunities for team members, provide constructive feedback, and tailor mentorship to individual needs. Give an example where your approach led to a team member’s success.

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What metrics do you use to measure team success?

Highlight specific metrics you consider critical for measuring engineering team success, such as code quality, delivery timelines, or team engagement levels. Sharing how you track and respond to these metrics can drive home your data-driven approach.

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How do you approach cross-functional collaboration?

Explain your strategies for fostering collaboration between engineering and other teams, such as regular check-ins, shared goals, and communication tools. Illustrating a collaborative project can highlight your effectiveness in cross-disciplinary environments.

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What excites you about the future of healthcare technology?

Share your passion for healthcare technology innovations and how they can improve patient outcomes. Discuss any relevant trends or developments in AI within healthcare that you find particularly interesting or inspiring, connecting your enthusiasm to Rad AI's mission.

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Our mission is to empower radiologists with AI — saving radiologists time, reducing burnout, and helping to improve the quality of patient care.

58 jobs
MATCH
VIEW MATCH
BADGES
Badge Bipoc LedBadge Flexible CultureBadge InnovatorBadge Rapid Growth
CULTURE VALUES
Mission Driven
Social Impact Driven
Inclusive & Diverse
Collaboration over Competition
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
INDUSTRY
TEAM SIZE
EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
March 19, 2025

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