About Accelerant

Accelerant is a data-driven risk exchange connecting underwriters of specialty insurance risk with risk capital providers. Accelerant was founded in 2018 by a group of longtime insurance industry executives and technology experts who shared a vision of rebuilding the way risk is exchanged – so that it works better, for everyone. The Accelerant risk exchange does business across more than 20 different countries and 250 specialty products, and we are proud that our insurers have been awarded an AM Best A- (Excellent) rating. For more information, please visit www.accelerant.ai.

About the Role 

Accelerant is seeking an experienced Director of Engineering to lead one of our full stack engineering teams within the Product & Technology group. This role combines people management with strong project management discipline and Agile practices. You will be responsible for developing engineering talent, managing cross team dependencies, and enabling your team to build high quality, impactful SaaS applications. 

Core Responsibilities 

• AI & Data Science Product Development: Lead projects that surface Data Science model outputs and GenAI capabilities into product features. Partner with data science, architects, and data teams on integration, implementation, and delivery of AI powered product capabilities. 

• AI Tooling & Adoption: Champion the adoption of AI tools and practices within the team. Evaluate and implement AI assisted development tools, establish best practices for AI augmented workflows, and drive measurable improvements in developer productivity. 

• Project Planning & Execution: Own end to end project delivery. Define scope, create realistic timelines, identify risks early, break down initiatives into milestones, and track progress against commitments. 

• Team Development & Mentorship: Invest in your team members by promoting continuous growth, offering guidance and support, and fostering a positive and inclusive work environment. 

• Agile Process Ownership: Serve as the Agile champion for your team. Ensure consistent execution of Scrum ceremonies, track sprint metrics, and refine processes to improve predictability. 

• Stakeholder & Dependency Management: Build relationships with business stakeholders, Product Management, Design, and partner engineering teams. Communicate status, manage expectations, flag risks early, and coordinate across teams to prevent blockers. 

• Technical Roadmap Ownership: Partner with the team Architect on technical direction and design decisions. Contribute to quarterly planning and OKR definition. Balance technical debt reduction with feature delivery. 

• Engineering & Operational Excellence: Drive engineering best practices and scalable solutions. Own production reliability, lead incident response and postmortems, and improve system stability. 

• Performance Management: Monitor and guide the performance of your team members, providing regular feedback and helping each individual reach their career potential. 

Technical Requirements 

• Full Stack SaaS Understanding: A solid understanding of full stack SaaS applications and best practices is necessary to effectively support and guide teams. 

• API Integration Experience: Strong experience consuming external APIs and integrating third party services. Understanding of API contracts, versioning, health monitoring, and production readiness requirements. 

• GenAI Development Expertise: Demonstrated experience building production features using LLMs and GenAI technologies, including prompt engineering, model integration, RAG patterns, agentic workflows, and guardrails. Ability to define and measure quality, accuracy, and observability metrics for GenAI features in production. 

• Machine Learning & Data Science Knowledge: Solid understanding of machine learning concepts, model deployment, and inference APIs. Ability to evaluate model accuracy and performance and collaborate effectively with Data Science teams with enough depth to challenge approaches and drive solutions. 

• Data Platform Familiarity: Familiarity with data pipelines and modern data platforms. Experience with Snowflake, data warehousing concepts, or similar technologies is a plus. 

• Familiarity with the Stack: Familiarity with our stack, which includes TypeScript (for both frontend and backend), Svelte, Node.js/Nest.js, AWS, and Infrastructure as Code (IaC), is preferred, though experience with similar technologies is also valuable. 

• Agile Tooling: Proficiency with Agile project management tools such as Jira, including workflow configuration, reporting, and dashboard creation. 

Qualifications 

• Experience: 5 to 7 years as an engineering manager, ideally leading cross functional teams in a SaaS environment. Track record of delivering complex software projects on time, including customer facing GenAI or ML powered features. 

• Agile Expertise: Deep understanding of Agile principles and Scrum methodology. Scrum Master or similar certification is a plus. 

• Cross Team Collaboration: Proven experience working with data teams, whether Data Science, Data Engineering, or Analytics. Ability to bridge technical discussions across different engineering disciplines. 

• Operational Mindset: Comfortable with on call responsibilities and production support. 

• Leadership Skills: Proven track record of effective team leadership, performance management, and fostering a positive, growth oriented environment. 

• Strategic Mindset: Strong analytical skills, able to make data driven decisions, and balance between hands on support and strategic planning. 

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