Accelerant

Paralegal

• Assist attorneys in preparing legal documents and correspondence
• Conduct legal research and analysis
• Manage and organize legal files and documents
• Assist attorneys in drafting various legal documents, including board resolutions
• Take meeting minutes and prepare board documentation
• Perform certain corporate secretarial duties
• Prepare presentations, reports, and summaries for a variety of audiences
• Prepare and submit regulatory and legal filings
• Review, track and monitor legislation and regulations that impact the company’s products and/or processes
• Update legal team with timely analysis and summaries of new legislation/regulations affecting the business
• Assist in developing automated processes for tracking regulatory changes and deadlines.

Insurance Regulatory Paralegal

Financial Planning and Analysis

• Serve as the trusted advisor and primary interface for leadership in Finance Operations function.
• Ensure IT investments and initiatives are directly aligned to Finance strategy and business goals.
• Build trust and foster strategic dialogue between Finance and Technology.
• Capture, elicit, and document Finance business requirements with precision and clarity.
• Translate business needs into actionable requirements, ensuring alignment with enterprise architecture.
• Hand-off requirements to technical delivery teams, while continuing to provide input and act as the business voice during design and build.
• Own and manage Finance products and capability roadmaps, ensuring priorities are visible, sequenced, and achievable.
• Define Finance capabilities, processes, and models to create a blueprint for aligning initiatives with enterprise strategy.
• Own all business outcomes delivered by BSGIT for Finance Operations function in Finance.
• Partner with delivery teams to ensure delivered solutions provide measurable business benefit.
• Act as the primary interface with Finance leadership, ensuring business needs and priorities are consistently represented.

Business Engagement Lead – Finance Operations

Data Scientist

• Lead analytics and investigations that help the business understand exposure patterns and accumulation risk
• Define and enforce data standards, quality controls, and best practices for exposure data across business lines
• Own data quality and completeness - you not only collect feedback, but intuit what needs to be fixed from your industry experience, and collaborate with other departments on permanent solutions to reliably produce best in class exposure data
• Lead the oversight into ingestion, transformation, and normalization of exposure data from internal and external sources
• Validate and QA exposure data: identify anomalies, gaps, duplicates, inconsistencies, and drive improvements
• Partner with actuarial, underwriting, catastrophe modeling, and product teams to understand their exposure needs
• Develop and maintain exposure data documentation, data dictionaries, and process guidelines
• Enable and support analytical use cases (e.g. accumulation risk, portfolio stress testing, scenario analysis)
• Build, monitor and track data quality KPIs, build dashboards or alerts to surface issues proactively
• Support ad hoc analysis to diagnose exposure trends and concentration risk
• Provide guidance on integrating exposure data into downstream tools (e.g. modeling engines, pricing systems, BI)

Exposure Data Manager

Solutions Engineer

• Sit inside delivery teams for the duration of engagements, not alongside them
• Attend design and development sessions, review technical decisions as they are being made
• Continuously assess whether what is being built conforms to Accelerant's architecture principles
• Propose better paths and help the team take them where documented patterns do not exist
• Make sound technical decisions quickly with available information
• Assess capabilities built by business users and create a clear path to production
• Design and validate integration patterns between enterprise systems and data platforms
• Collaborate with the Data Office to ensure data products are accurate and accessible
• Document technical decisions and ensure architectural decision records exist and are accessible

Forward Deployed Data Solution Engineer

SDET

• Drive the test automation initiative
• Own the test automation roadmap end to end. Set the strategy, prioritize the work, and drive execution across the team. You'll partner with QA and engineering on what we automate, how, and when.
• Scale the foundational framework
• A Playwright/JavaScript framework is already built. Take it from foundational to enterprise-grade, with a focus on performance, stability, and reusability.
• Expand coverage breadth and depth
• Push automation into areas that may not have any QA support today, and deepen regression coverage on core systems: Salesforce, MuleSoft, D365 Power Apps, D365 F&O, DCR, and Tagetik.
• Implement a scalable design and review process
• Help build the design and review process that keeps automation quality high as the suite and the team grow - test design standards, code review norms, framework contribution guidelines.
• Scale test execution and reporting
• Build the infrastructure that runs tests fast, reports results clearly, and surfaces signal over noise. Parallel execution, smart retries, actionable dashboards.
• Build specialized QA agents using Cursor AI
• Design and ship AI agents for performance testing, regression analysis, and defect triage (to name a few). Use Cursor as your build environment. Treat the agents as products solving specific problems.
• Host QA agents on the AI fabric
• Partner with the AI platform team to deploy your agents on the org's AI fabric. Make them discoverable, governed, and reusable across functions.

Senior Software Development Engineer in Test, SDET

AI Engineer

• Work directly with key stakeholders in a consultative manner to identify pain points and start building solutions to simplify manual and redundant workflows.
• Write the production code — this isn't a strategy role.
• Build agents to automate grind.
• Partner with function heads to design, test, and deploy AI-driven agents and workflow automations.
• Own evals, observability, guardrails, and the 'is this thing actually working' layer.
• Use AI coding assistants (e.g. Claude, Replit, Vercel, etc.), low/no-code platforms, and workflow automation tools to rapidly build and ship MVPs.
• Own cloud infrastructure, CI/CD, and operational reliability for what you ship.
• Lead vendor evaluations, negotiate modular solutions, and ensure clean integration with our data and AI platforms.

Forward Deployed AI Engineer

Full-stack Engineer

• Designing and building front-end interfaces for internal operational tooling, including dashboards, data observability views, and stakeholder communication surfaces
• Developing rich data visualizations that surface pipeline health, data quality metrics, and business KPIs to technical and non-technical audiences
• Building and maintaining backend services that support operational tooling, integrating with data infrastructure such as Snowflake, dbt, and monitoring platforms
• Collaborating closely with data engineers, analytics engineers, and business stakeholders to translate data observability requirements into intuitive, high-quality interfaces
• Working independently as a software engineer within a data-focused team, driving technical decisions for the tooling layer while leveraging other full stack teams across the organization for guidance and support
• Shipping iteratively, balancing speed of delivery with code quality, maintainability, and scalability

Full Stack Software Engineer – Data Observability, Operational Tooling

Technical Product Manager

• Own the enterprise AI roadmap: Define a living backlog of applications to build, and workflows to automate, ranked by time saved and pain eliminated.
• Build agents to automate grind.
• Partner with function heads and AI engineers to design, test, and deploy AI-driven agents and workflow automations that eliminate manual effort and capture quantifiable savings.
• Build the Accelerant Enterprise OS: Own our central AI-powered hub for all internal custom tooling, data, and insights – integrating role-aware agents, dashboards, and workflow automation.
• Prototype & iterate fast: Use low/no-code and AI workflow automation tools (E.g., Claude Managed Agents, Replit) to build and ship MVPs rapidly.
• Drive build-vs-buy rigor: When internal builds aren’t the right choice (i.e., due to feasibility, speed to market, costs), lead vendor evaluations, negotiate modular solutions, and ensure clean integration with our data and AI platforms.
• Drive actual adoption: Shipping a tool is the easy part. Getting people to change how they work is hard. You'll lead the education, documentation, and change management that makes adoption happen.