Senior Manager, AI
New
This is a remote-first roleFull-TimeManager
Salary$220,000 to $245,000 annually
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Job Details
- Experience
- 10+ years of software engineering experience, including 3+ years leading and developing high-performing engineering teams.
- Required Skills
- LeadershipSoftware EngineeringMLOpsDistributed Systems
Requirements
- 10+ years of software engineering experience, including 3+ years leading and developing high-performing engineering teams.
- Experience building and scaling production AI-powered applications and platforms.
- Expertise in machine learning infrastructure, model deployment, and operational excellence.
- Strong experience designing scalable data architectures and distributed systems.
- Strong software engineering fundamentals with experience building cloud-native applications using modern programming languages and infrastructure tooling.
- Proven ability to define technical strategy, establish engineering best practices, and influence technical direction across multiple teams.
- Excellent cross-functional leadership skills with experience partnering closely with Product, Data Science, Clinical, and Architecture teams.
- Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
- Healthcare experience is a plus.
Responsibilities
- Lead, manage, and grow a distributed engineering team, fostering technical excellence, accountability, and a culture of mentorship and continuous improvement.
- Own the technical strategy and roadmap for AI platforms, applications, and agents, partnering with Enterprise Architecture to deliver scalable, reliable, and observable systems.
- Design data, retrieval, and semantic architectures that provide AI agents with accurate, contextual information across complex healthcare data sources.
- Drive architecture for model serving, inference optimization, and production AI systems while establishing MLOps best practices for deployment, monitoring, experimentation, and performance.
- Partner with product, ML, data science, and architecture teams to translate business needs into scalable technical solutions.
- Drive agile delivery, define engineering quality and reliability metrics, and champion operational excellence, security, and HIPAA-compliant platform design.
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