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.
Location: Remote
Department: Product & Technology
Reports to: Director of Engineering
Product Area: Insights Analytics & Workflows
Job Description
Accelerant is seeking a Product Area Lead Architect to provide hands-on operational architectural leadership for our Insights Analytics & Workflows product area. This role operates at a Principal level influencing architecture and execution across multiple autonomous product teams. You will work closely with team architects, engineering managers, product managers, and Data Science teams to ensure teams move fast without fragmenting the architecture.
This is not an ivory tower architecture role. It is highly collaborative, pragmatic, and operational-focused on identifying architectural gaps, managing dependencies, and enabling teams to execute confidently within a shared architectural framework. You will champion standards-based architecture, leveraging web standards, open protocols, and industry conventions to build interoperable, accessible, and future-proof systems.
Key Responsibilities
Operational Architectural Leadership
- Ensure architectural alignment across product teams, partnering closely with team architects and engineering managers.
- Proactively identify architectural gaps, technical debt, and quality risks, drive resolution through collaboration and influence.
- Manage cross-team technical dependencies to enable independent parallel execution.
- Translate architectural strategy into clear actionable guidance that teams can apply sprint by sprint.
Cross Team Coordination & Alignment
- Facilitate architectural discussions and resolve technical conflicts across teams through principled, pragmatic decision-making.
- Act as an escalation point for complex cross-team technical challenges.
- Ensure architectural decisions are clearly communicated, understood, and consistently applied.
Design & Innovation
- Define and maintain architectural patterns across backend services, APIs, data platforms, and front-end systems.
- Design scalable, resilient systems for analytics, workflow orchestration, and intelligence features.
- Guide decomposition of legacy systems into well-defined services and domains.
- Evaluate technologies and data stores, favoring open standards and long-term maintainability.
- Architect distributed systems with a focus on reliability, fault tolerance, and scalability.
Standards & Governance
- Establish API design standards ensuring consistency, discoverability, and ease of integration.
- Define front-end standards prioritizing web platform capabilities, progressive enhancement, and accessibility (WCAG).
- Create governance frameworks that balance standardization with team autonomy.
- Drive adoption of industry standards: OAuth2, OpenID Connect, OpenTelemetry, JSON API over proprietary alternatives.
Technical Leadership
- Partner with engineering teams on design reviews, PR reviews, and implementation guidance.
- Establish standards for cross-cutting concerns: API versioning, auth, observability, error handling, and resiliency patterns.
- Collaborate with platform and DevOps teams on containerization, CI/CD, and cloud-native deployment.
- Produce clear technical design documentation that drives alignment and knowledge sharing.
- Mentor engineers and raise the overall architectural maturity of the organization.
GenAI ML & AI Architecture
- Architect customer-facing GenAI features using LLMs, including RAG pipelines, prompt engineering frameworks, and conversational AI interfaces.
- Define patterns for ML model integration, serving endpoints, API contracts, versioning, and health monitoring.
- Partner with Data Science to translate models into production-grade features with clear integration contracts and deployment workflows.
- Establish standards for responsible AI including evaluation criteria, privacy guardrails, and LLM output validation.
AI Transformation & Productivity Leadership
- Scale AI-driven development workflows across teams, ensuring engineers leverage AI coding tools effectively.
- Guide team architects and coach senior engineers on using AI tools to enhance productivity and code quality.
- Work hands-on with teams to identify opportunities for AI to solve operational challenges and improve velocity.
Solution Evaluation & Quality Assurance
- Evaluate and recommend technologies to enhance capabilities across analytics, workflow, and intelligence domains.
- Ensure architectural integrity through code reviews, assessments, and continuous monitoring.
- Proactively identify technical risks and devise strategies for reliability, security, and performance.
Technical Requirements
- Full Stack SaaS Architecture: Strong proficiency in modern JavaScript, TypeScript, and Node.js.
- Deep knowledge of web platform fundamentals and browser native capabilities.
- Experience designing and evolving well-structured APIs for platform integrations.
- Architectural & Systems Thinking: Deep knowledge of architecture principles, design patterns, and distributed systems.
- Proven ability to make pragmatic tradeoffs in complex, evolving systems.
- Experience in cloud-native environments, preferably AWS.
- AI Enabled Engineering: Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, Claude, etc.).
- Understanding of AI applications for development productivity and code quality improvement.
Qualifications
- 8 to 12 years in software engineering and architecture roles.
- Proven experience operating across multiple agile teams in an architectural leadership capacity.
- Track record of managing cross-team dependencies and bridging architectural vision with day-to-day execution.
- Proven ability to drive AI adoption and transformation within engineering organizations.
- Excellent communication and facilitation skills with the ability to align work across distributed teams.
- Pragmatic operational mindset with strong problem-solving abilities.
- Bachelors or Masters degree in Computer Science, Engineering, or a related field.
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