Director of Engineering - Inference Platform

About the job

Responsibilities

• Lead, grow, and inspire a software team, fostering a culture of technical excellence, collaboration, and continuous improvement.
• Own hiring for your team: define roles, assess candidates, and build a diverse, high-performing engineering organization.
• Drive the career development of your engineers through regular 1:1s, meaningful feedback, and clear growth plans.
• Set clear goals and expectations, track team progress, and remove blockers to keep the team executing effectively.
• Partner with Product, ML, QA, and DevOps leadership to align team priorities with broader organizational objectives.
• Contribute directly as a software engineer: designing systems, writing code, and leading implementation on critical platform initiatives.
• Participate in and lead design reviews, providing authoritative technical guidance on major features and cross-cutting changes.
• Establish and uphold engineering standards, best practices, and coding quality across the team.
• Proactively identify and drive the resolution of systemic risks: performance bottlenecks, reliability gaps, and scaling constraints.
• Stay current on emerging technologies and AI inference trends to inform the team's technical direction.

Requirements

• 12+ years of software engineering experience, including 2+ years leading and managing engineering teams.
• Demonstrated ability to manage, develop, and hire strong engineers while remaining a hands-on technical contributor.
• Strong technical depth in backend systems built with Python, Go, or Rust.
• Experience with AI inference serving, orchestration, and the infrastructure challenges of LLM workloads at production scale.
• Proven ability to drive engineering excellence across an engineering team.
• Excellent communication skills: able to work effectively with engineers, cross-functional partners, and senior leadership.
• Experience running iterative engineering processes in a fast-paced environment.
• Experience with Kubernetes ecosystem tooling, including Operators and Helm Charts.
• Background in ML application optimization and productionization.
• Experience building or managing teams that deliver cloud-native platforms for enterprise customers.
• Familiarity with AI coding assistants and the developer tooling ecosystem.
• Experience at a high-growth AI infrastructure company.

Benefits

• Competitive total rewards package