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Owns and evolves cloud-native software architectures on AWS for modern SaaS products. Responsibilities include designing scalable applications, microservices, APIs, event-driven and serverless solutions; establishing architecture standards; guiding security, reliability, observability, CI/CD, and infrastructure practices; leading architecture reviews and proofs of concept; and coaching engineers and technical leads. The role requires deep expertise in .NET, AWS, distributed systems, modern front-end development, databases, containers, and infrastructure as code.

Leads enterprise incident response activities, including investigating alerts, responding to medium- and high-severity security incidents, threat hunting, mentoring junior staff, and coordinating tabletop exercises. Tracks post-incident actions, reports lessons learned, improves response tools and processes, and collaborates with Threat Management, Legal, and Privacy teams. The role requires strong knowledge of incident response procedures, threat actor tactics, security tooling, operating systems, networking, cloud, and virtualization.

Performs catastrophe and risk analyses for insurance and financial clients, resolves product and modeling questions, delivers client training, manages consulting projects, supports onboarding and pre-sales activities, and provides feedback for product development. The role builds client relationships, coordinates deliverables, supports model change management, and represents Verisk at industry events.

Develop and maintain secure, scalable C#/.NET services, REST APIs, microservices, frameworks, and engineering tools. Contribute to architecture decisions, system reliability, CI/CD, automated testing, observability, incident response, and production support. Collaborate cross-functionally, mentor developers, conduct code reviews, reduce technical debt, and improve system performance, security, and maintainability. Participate in on-call rotations and use AI-assisted development tools responsibly.

Design, develop, test, debug, document, and maintain full-stack software for a B2B remodeling-project product. Complete projects independently, participate in architecture discussions, and improve team quality through code reviews, pairing, and knowledge sharing. Engage with customer feedback, usage data, and feature adoption. Use AI-assisted development tools daily while contributing to maintainable, flexible production software.

Leads the Marketing PMO, managing project managers and overseeing portfolio intake, prioritization, governance, resource planning, project delivery, vendor relationships, budgets, reporting, and executive communications. The role drives operational excellence across marketing and shared services by establishing scalable processes, monitoring capacity and performance, resolving risks, and aligning cross-functional initiatives with organizational priorities.

Lead Verisk Marketing’s UX and digital experience capability by designing user-centered websites, landing pages, campaigns, emails, and interactive assets. Establish UX standards, accessibility guidelines, design systems, reusable components, and AI-enabled workflows. Coach designers, provide creative direction, and partner with Marketing, Product, Technology, and business teams to improve usability, engagement, consistency, and delivery efficiency across digital channels.

The Senior Software Engineer will design AI features, maintain data pipelines, develop scalable ML serving infrastructure on AWS, and lead cloud-native software solutions.

Designs and maintains comprehensive QA strategies, test plans, and automated test suites for casualty catastrophe and liability risk analytics. Performs functional, integration, regression, end-to-end, REST API, system-level, and data-driven testing. Validates scientific and financial models, documents analytical work in Python and R, partners with developers and stakeholders, and improves automation frameworks and quality practices within Agile Scrum teams.

Configure, implement, test, and optimize AI-powered insurance solutions across FAST and cloud AI platforms. Responsibilities include prompt engineering, model selection, troubleshooting, performance monitoring, documentation, customer engagement, usage analysis, and translating business needs into technical configurations. Collaborate with product owners, engineers, and customers on AI implementations, agile ceremonies, backlog refinement, and product improvements.