aledade - Senior Engineering Manager- AI Data Platform

• 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. • Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.