Senior Engineering Manager- AI Solutions

Remote, United States

Aledade

Aledade works with independent practices, health centers, and clinics to build and lead Accountable Care Organizations (ACOs) anchored in primary care.

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As the Senior Engineering Manager in AI Solutions, you will lead by being a highly technical leader who delivers high business impact on ML/AI projects of increasing dependencies and ambiguity. 
You will lead a team of senior ML Engineers in the development of technology that saves lives and improves mental and physical health for millions of people. 
At Aledade, we empower primary care physicians with technology to keep their patients healthy, preventing unnecessary hospitalizations.

Primary Duties:

  • Build a high performing team by hiring and nurturing engineering talent.
  • Strong technical leadership - drive technical solutioning and building roadmaps.
  • Set aggressive and clear goals and remove all roadblocks for the team to achieve them.
  • Working seamlessly and collaboratively with stakeholders across Aledade to achieve business outcomes.
  • Work closely with engineering leaders to drive engineering excellence in our processes and systems.

Minimum Qualifications:

  • BS/BTech (or higher) in Computer Science, Engineering or a related field required.
  • 10+ years of production-level experience as an engineer and technical lead building highly scalable and reliable software. 
  • 5+ years of managerial experience building and leading technical engineering teams.

Preferred KSA’s:

  • You have experience in attracting, hiring, and coaching world-class engineers including performance management.
  • You have experience in taking ownership of the technology decisions, while delegating and empowering team members.
  • You have experience communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training.
  • You have strong communication and relationship building skills, with experience influencing and aligning multiple stakeholders.

  • Domain specific Preferred KSA’s:AI/ML:
  • Strategic Vision: Proven ability to craft and execute a strategic vision for an AI/ML-focused team, particularly in applying AI-enabled workflows in healthcare/enterprise settings. Experience in aligning day-to-day AI/ML development efforts with long-term strategic goals.
  • Technical Expertise:
  • 7+ years of experience in machine learning related technologies, with a strong preference for Python.
  • Extensive experience in designing and implementing secure, scalable, and maintainable AI/ML platform architectures.
  • Proficiency in distributed systems, microservices, containerization technologies (e.g., Docker, Kubernetes), model training infrastructure, orchestration tools, and MLOps principles.
  • Planning and Communication: Demonstrated experience in translating business objectives into technological roadmaps, aligning short-term actions with long-term strategic goals, and effectively communicating these plans to both technical and non-technical stakeholders.
  • Skilled at aligning short-term AI/ML initiatives with long-term strategic goals and communicating these plans effectively to both technical and non-technical stakeholders.
  • Research Orientation: Familiarity with current AI/ML research trends and the ability to translate published advancements into practical healthcare applications.
  • Mentorship: Proven track record of mentoring and developing AI/ML talent within engineering teams.
  • Collaborative Leadership: Exceptional skills in working effectively with cross-functional teams, including product managers, designers, data scientists, and clinical staff.
  • Data-Driven Decision Making: Ability to leverage data-driven insights to inform engineering and research roadmaps, resource allocation, and strategic planning.
  • Business Acumen: Ability to prioritize AI/ML platform features that meet business needs while maintaining security, scalability, and performance.
  • Startup experience: Understanding of the fast-paced, dynamic environment of a startup is highly valuable.

Physical Requirements:

  • Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture Computer Science Distributed Systems Docker Engineering Kubernetes Machine Learning Microservices MLOps Model training Python Research Security

Perks/benefits: Startup environment

Regions: Remote/Anywhere North America
Country: United States

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