Director of Engineering

Recruiting From Scratch•San Francisco, NY

4d•Remote

About The Position

We’re representing a venture-backed AI company building professional-grade AI systems for the $7T global insurance industry. The company develops technology that can read, reason, decide, and act within complex insurance workflows, helping augment human professionals today while enabling increasing levels of automation over time. Its products are already in production with leading insurers and are driving measurable outcomes across critical business functions. The broader vision is to build the AI operating system for decision-making across insurance. Backed by investors including IA Ventures and Inspired Capital, the team brings experience from companies such as Facebook, Palantir, Google, Amazon, Uber, Mastercard, and McKinsey. The company operates with a high-performance culture centered around ownership, customer impact, technical excellence, transparency, and rapid experimentation.

Requirements

10+ years of professional software engineering experience.
3+ years of full-time engineering people management experience.
Experience leading substantial full-stack product engineering organizations.
Ideally has experience managing engineering managers and scaling engineering teams beyond a single IC team.
Remains deeply technical and can credibly engage in architecture, system design, infrastructure, and engineering trade-off discussions.
Proven track record leading complex, large-scale engineering initiatives.
Strong experience connecting technical strategy to company-level product and business objectives.
Deep architectural expertise across distributed systems, scalable infrastructure, and modern cloud environments.
Experience overseeing platforms using technologies such as AWS Lambda, EC2, serverless architectures, and asynchronous workflows.
Track record of building high-performing, results-oriented engineering organizations.
Strong recruiter who can consistently attract exceptional engineering talent.
Experience establishing engineering standards, operating rhythms, and metrics as an organization scales.
Able to make pragmatic trade-offs between speed, technical quality, reliability, and longer-term architecture.
Comfortable operating with significant autonomy in a fast-growing environment.

Nice To Haves

Experience managing managers and multiple engineering teams.
Background scaling a technically complex B2B or enterprise SaaS product.
Experience with AI-native products or engineering organizations incorporating AI agents heavily into software development.
Strong point of view on how AI changes engineering productivity, development processes, and team structure.
Experience building systems where correctness, reliability, security, and customer trust are critical.
Experience scaling distributed and serverless architectures.
Strong metrics orientation around engineering velocity, reliability, quality, and organizational performance.
Experience partnering directly with founders, executives, and senior Product leadership.
Comfortable remaining technically involved while operating at Director-level organizational scope.
Insurance or insurtech experience can be valuable, but is not presented as a requirement.

Responsibilities

Lead and grow the Core Product engineering organization, owning both technical direction and team performance.
Partner closely with the executive team, Product, and other cross-functional leaders to translate company strategy into an engineering roadmap.
Define the architectural roadmap for a platform powering AI-assisted and increasingly autonomous insurance workflows.
Bridge product vision and technical execution, ensuring engineering investments translate directly into customer and business impact.
Establish engineering frameworks, standards, processes, and operating cadences that allow the organization to scale effectively.
Drive complex, large-scale engineering initiatives from strategy through execution.
Develop a high-performance engineering culture with clear accountability for quality, reliability, velocity, and outcomes.
Recruit, retain, coach, and develop exceptional engineering talent, including engineering managers and senior technical leaders.
Raise the bar for architecture, system design, code quality, operational excellence, and engineering execution.
Establish and use engineering metrics to identify bottlenecks, improve execution, and make better technical and organizational decisions.
Oversee the evolution of distributed, cloud-based systems utilizing serverless technologies and asynchronous workflows.
Help rethink how software is built as AI agents become increasingly embedded within the engineering lifecycle.
Balance speed and experimentation with the reliability and quality requirements of software used by major enterprise customers.