AI Accelerated Platform Engineering

LimeIQ is an innovative Fin Tech/Insur Tech platform transforming how the global insurance market ingests, validates, aggregates, and analyzes complex operational data. We serve managing agents, brokers, underwriters, and delegated authorities operating in the Lloyd’s of London and specialty insurance markets.

At the core of our platform is Lincoln Smart™, a proprietary ingestion and transformation engine built for high-volume bordereaux (BDX) processing. Our platform automates reconciliation, validation, and standardization of fragmented insurance submissions into a centralized and trusted data foundation.

LimeIQ is aggressively investing in AI-driven software engineering, intelligent automation, and accelerated product delivery. We are building an engineering organization that uses modern AI tooling to dramatically improve development speed, testing, architecture design, documentation, operational support, and data engineering productivity while maintaining enterprise-grade quality and auditability.

Our mission is to become the leading insurance data intelligence platform through disciplined engineering, deep domain expertise, and AI-accelerated software delivery.

We are seeking an AI API Engineer who thrives in a modern AI-assisted engineering environment and can leverage emerging AI development tooling to accelerate API and backend service delivery without compromising reliability, scalability, or maintainability.

This is a hands-on role spanning API design, backend services, data integration, and intelligent automation. The ideal candidate understands how to combine strong engineering fundamentals with AI-enhanced workflows to dramatically improve productivity across API design, coding, testing, debugging, documentation, and operational support.

You will play a key role in modernizing insurance data integration through AI-assisted development practices, scalable cloud-native API architecture, and advanced automation across LimeIQ’s ingestion, validation, reconciliation, and analytics platforms.

• Leverage AI-powered development tools to accelerate API design, coding, testing, debugging, documentation, and code reviews.
• Design, develop, and scale AI-accelerated RESTful and event-driven APIs using Python, FastAPI, and modern cloud-native architectures.
• Develop and optimize scalable backend services, integration APIs, and distributed data processing pipelines.
• Build intelligent automation workflows that reduce manual engineering effort and improve API delivery velocity.
• Architect API integration layers connecting Lincoln Smart, Microsoft Fabric, and downstream analytics platforms.
• Implement robust authentication, authorization, validation, and exception-management frameworks for complex insurance datasets.
• Apply AI-assisted approaches to API quality, automated test generation, contract testing, and operational monitoring.
• Collaborate with product, data, Dev Ops, and BI teams to rapidly deliver high-quality platform capabilities.
• Participate in architecture reviews, technical planning, and modernization initiatives focused on scalability and engineering efficiency.
• Contribute to API design standards, reusable frameworks, and AI-enabled development best practices.
• Support modernization of legacy integrations while reducing technical debt and operational complexity.

• Strong practical experience using AI-powered software engineering tools and workflows
• Ability to rapidly prototype, iterate, and deliver software using AI-assisted development practices
• Experience integrating AI into development life cycles while maintaining code quality, security, and auditability
• Understanding of prompt engineering, AI-assisted debugging, automated test generation, and developer productivity tooling
• Experience with Python or Django in production environments, including REST framework or FastAPI
• Strong understanding of API design, versioning, OpenAPI/Swagger documentation, and performance optimization
• Experience implementing authentication and authorization patterns (OAuth2, JWT, API gateways)
• Hands-on experience building ETL pipelines and integration APIs with PySpark and cloud analytics platforms
• Strong understanding of data normalization, reconciliation, validation, and auditability
• Experience handling high-volume insurance, financial, or operational datasets
• Experience with Microsoft Azure, Microsoft Fabric, and API management services
• Familiarity with CI/CD pipelines,…