Accelerant
201 - 500 employees
Founded 2018
☁️ SaaS
🤝 B2B
💰 $150M Private Equity Round - Accelerant on 2023-06
SaaS • B2B
Accelerant is a digital-first risk exchange and insurance platform that connects managing general agents (MGAs), underwriters, reinsurers, and institutional capital through a tech-powered, data-driven marketplace. The platform provides real-time analytics, underwriting tools, performance metrics, and operational support (actuarial, claims, regulatory) to streamline specialty insurance distribution and enable faster, more transparent capital deployment. Accelerant positions itself as a SaaS-style partner for specialty insurance firms, focused on improving efficiency, transparency, and profitable growth.
AI Platform Engineer – Global
🕒 April 1
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Accelerant
201 - 500 employees
Founded 2018
☁️ SaaS
🤝 B2B
💰 $150M Private Equity Round - Accelerant on 2023-06
SaaS • B2B
Accelerant is a digital-first risk exchange and insurance platform that connects managing general agents (MGAs), underwriters, reinsurers, and institutional capital through a tech-powered, data-driven marketplace. The platform provides real-time analytics, underwriting tools, performance metrics, and operational support (actuarial, claims, regulatory) to streamline specialty insurance distribution and enable faster, more transparent capital deployment. Accelerant positions itself as a SaaS-style partner for specialty insurance firms, focused on improving efficiency, transparency, and profitable growth.
📋 Description
• Build production AI agents and services • Develop reusable AI components and workflows • Prototype and productionize AI use cases • Support development teams on AI implementations • Collaborate with Compliance and ARX PS teams • Co-own AI workflow environments (e.g., n8n) with DevOps • Contribute to AI pattern development alongside AI Platform Architect • Maintain reference implementations • Improve AI reliability and observability • Design and implement Retrieval-Augmented Generation (RAG) pipelines • Implement prompt management, versioning, and evaluation tooling • Establish AI observability, monitoring, and cost tracking practices
🎯 Requirements
• 6–8+ years software engineering experience • Production AI implementation experience • LLM integration experience • Prompt engineering expertise • Experience building agents or AI workflows • Experience with vector databases and API orchestration • Strong systems thinking
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