Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading enterprise work management technology company is seeking an experienced engineering leader to oversee its AI Platform organization. The organization develops foundational systems that power AI experiences, with a focus on retrieval, knowledge extraction, model serving, inference infrastructure, AI evaluation, and efficiency.
The Director of Engineering will lead multiple engineering teams through their managers and establish the strategy, execution, and architecture that define how humans and AI work together to deliver trusted, reliable, and high-value workflows for enterprise customers worldwide.
The role is based in the San Francisco office and follows an office-centric hybrid schedule. Standard in-office days are Monday, Tuesday, and Thursday, with work-from-home flexibility on Wednesdays for most employees. Friday arrangements depend on the nature of the work and team collaboration requirements.
What You’ll Achieve
- Lead the multi-year vision and technical strategy for the AI platform, covering retrieval, agent context, model serving, inference, model portfolio strategy, and evaluation systems.
- Optimize AI infrastructure costs by managing model selection, routing, open-weight versus frontier model trade-offs, inference optimization, caching, and prompt efficiency.
- Establish AI evaluation frameworks, regression prevention mechanisms, and performance standards that make quality, cost, and latency measurable and dependable across product teams.
- Lead and mentor engineering managers and their teams across San Francisco and New York City.
- Build autonomous engineering organizations, recruit top talent, develop leaders, and maintain high execution standards.
- Evaluate when to adopt frontier models versus open-weight models and develop provider strategies that reduce vendor lock-in.
- Provide architectural leadership by evaluating technical decisions, assessing build-versus-buy opportunities, and serving as a trusted technical authority for AI infrastructure.
- Partner with product, go-to-market, and finance leaders to connect platform investments with business performance, unit economics, and enterprise trust.
- Establish the AI platform as a reliable, economical, and high-performance foundation for agentic enterprise software.
About the Candidate
- 12+ years of software engineering experience.
- 5+ years of engineering leadership experience.
- 2+ years of experience managing engineering managers.
- Proven experience building and developing organizations, including hiring and mentoring engineering managers and restructuring teams as organizational missions evolve.
- Strong experience using AI tools and technologies in daily engineering workflows.
- Deep expertise in serving architectures, inference providers, agentic frameworks, RAG architectures, and large-scale evaluation systems.
- Proven experience optimizing infrastructure costs and unit economics at scale, supported by measurable results and well-defined technical trade-offs.
- Strong platform engineering mindset focused on building trust, establishing clear standards, providing responsive support, and using data to guide engineering priorities.
- Excellent asynchronous communication skills and experience leading distributed teams across multiple time zones through strategy documents and decision memos.
- Strong decision-making skills with the ability to take clear, evidence-based positions while adapting quickly as new information becomes available.
Disclaimer
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