Director of Engineering (Platform Intelligence)
Location: Remote
Department: Product & Technology
Reports to: Director of Engineering
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.
Confidential
About Accelerant
Accelerant is a data-driven, technology-fueled insurance platform that empowers
underwriters to more effectively serve their insureds. We're using advanced data
intelligence tools to rebuild the way that underwriters share and exchange risk. With a
current focus on the small and medium-sized businesses that power our global
economy and their niche insurance needs, we align incentives to improve outcomes for
everyone. Our full-service risk exchange supports our carefully selected, best-in-class
network of underwriting teams. We leverage granular information on each policy to
deliver unprecedented insight into insurance pools, and our specialty portfolio is fully
diversified with very low catastrophe, aggregation or systemic risk. We're proud to have
been awarded an AM Best A- (Excellent) rating. For more information, please visit
www.accelins.com.
Accelerant is a fully remote company. Work where you're most productive and fulfilled.
This position is open to remote candidates across the U.S., Canada, UK, and Europe,
who have the flexibility to work with our teams distributed across Europe and North
America. Most cross-team collaboration happens in the mornings of the Eastern Time
Zone.