Product Area Lead Architect; EU, UK

Position: Product Area Lead Architect (EU, UK, US)
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 (Use the "Apply for this Job" box below)..

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 and 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 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, Open Telemetry, 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 Dev Ops 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…