Job Description
This job was selected by the SpringCube team to help AI, Data and Cloud Engineers discover relevant San Francisco Bay Area employers. Sign up to view the full employer details and apply directly with the hiring company.
Company Overview
A technology company focused on advancing artificial intelligence through innovative model architectures and efficient, large-scale foundation models. The organization combines expertise in AI research, systems engineering, and product development to build and deliver advanced AI models and experiences.
Responsibilities
- Build, lead, and develop a high-performing engineering team through hiring, coaching, performance management, and career development.
- Own the team’s technical roadmap, key decisions, and outcomes while establishing clear priorities and maintaining a consistent shipping cadence.
- Provide technical leadership across architecture, design reviews, complex technical challenges, and production incidents.
- Develop a deep understanding of the systems owned by the team and their technical tradeoffs to challenge assumptions, make informed decisions, and remove blockers.
- Partner closely with Product, Research, and other engineering teams to establish technical direction and deliver against organizational priorities.
- Ensure the team’s systems can scale with business growth while maintaining high standards for performance, reliability, observability, and engineering quality.
Qualifications
- Experience managing and developing high-performing engineering teams, including coaching, performance management, and career development.
- Strong technical depth and engineering judgment, with the ability to establish credibility with experienced engineers and participate deeply in architecture and technical decisions.
- Proven experience leading teams through complex technical projects in fast-moving and ambiguous environments.
- Strong ownership and prioritization skills, including the ability to make difficult tradeoffs and balance near-term execution with longer-term technical investments.
- Experience building and operating large-scale distributed systems with demanding performance, reliability, and observability requirements.
- Strong cross-functional leadership skills and the ability to align stakeholders around technical decisions and priorities.
- Experience building or scaling engineering teams during periods of rapid organizational growth or change is a plus.
- Background in machine learning, AI infrastructure, or generative models is a plus.
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