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The IND Lead Software Engineer develops hybrid mobile app solutions, collaborates in Agile teams, and ensures system performance and stability following coding standards.

The IND Lead Software Engineer will develop and maintain software in Guidewire ClaimCenter, troubleshoot issues, mentor team members, and integrate systems within Agile environments.

Handle a caseload of complex general liability bodily injury and property damage claims from inception to resolution. Investigate, evaluate coverage and liability, set reserves, manage litigation and defense counsel, attend trials/mediations, develop resolution strategies, prepare reports, and collaborate with business partners to address claim trends.

Develop and support scalable omnichannel contact center solutions using Amazon Connect, AWS cloud services, Python, APIs, microservices, and serverless architectures. Build IVR flows, routing logic, telephony integrations, and voice, chat, and email capabilities. Implement CI/CD automation, testing, observability, and secure integrations while contributing to Agile delivery, contact center modernization, production support, and AI-enabled customer experience capabilities.

Designs, develops, publishes, and maintains accessible, responsive web pages and digital campaigns. Responsibilities include creating wireframes, mockups, prototypes, graphics, HTML/CSS, and JavaScript enhancements; managing CMS and DAM content; updating data-driven product pages; performing QA; supporting redesigns and rebrands; and collaborating with marketing, IT, product, and compliance teams. The role also uses AI-assisted development tools and requires strong attention to detail, project management, and communication skills.

Supports financial advisors by explaining mutual fund and ETF products, creating web-based illustrations, handling inquiries, ordering marketing materials, tracking calls, and coordinating between home-office teams and field wholesalers. After obtaining required licenses, conducts outbound advisor calls about products, marketing ideas, and meetings. The role includes training support and requires strong communication, organization, PC skills, and adaptability.

Leads 5–6 underwriters supporting profitable acquisition and retention of group life, disability, and supplemental health reinsurance clients. Oversees presale, new business, and renewal underwriting; ensures adherence to guidelines, pricing, authority, and documentation standards. Develops team capability through coaching and performance management, monitors profitability and underwriting metrics, communicates decisions to clients and partners, recommends product and pricing changes, and manages client implementations and strategic projects.

Modernize enterprise Java applications and build secure, scalable cloud solutions across AWS and GCP. Lead infrastructure standards, Infrastructure as Code, CI/CD, observability, deployment automation, and production readiness. Develop GenAI and agentic AI solutions using Vertex AI and Google ADK, including development agents, test agents, and workflow automation. Partner with business, architecture, security, and engineering stakeholders, while mentoring engineers and advancing reusable enterprise engineering practices.

Supports reinsurance portfolio delivery through stakeholder interviews, requirements elicitation, documentation, user stories, acceptance criteria, process flows, data mapping, and backlog refinement. Partners with product, development, QA, and end-user teams in Agile delivery models. Applies ceded reinsurance knowledge to validate business needs, clarify testing requirements, support defect triage, and contribute to sprint delivery within a multi-vendor environment.

The Staff Data Reliability Engineer ensures data integrity, quality, freshness, and availability across enterprise pipelines. Responsibilities include defining data SLOs, implementing observability, building resilient Informatica and Python/PySpark pipelines, automating validation and recovery, eliminating operational toil, leading data incidents and postmortems, creating runbooks, and applying AIOps, machine learning, and DataOps practices to detect anomalies and self-heal data workflows.