LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® ...
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As an Engineering Manager, you will lead the development and operation of modern SaaS solutions while fostering an AI-first engineering culture. You will combine hands-on technical leadership with people management, helping teams deliver high-quality software, adopt AI-enabled engineering practices, and continuously improve development processes and outcomes.
Responsibilities
Use Claude Code, Codex, GitHub Copilot, or other approved AI coding tools to plan, build, refactor, test, debug, review, and document production software.
Establish practical guardrails for AI-generated code, including repo-level instructions, review standards, secure coding expectations, automated checks, and clear human accountability.
Guide ideas from discovery and proof of concept through technical design, implementation, validation, release, and continuous improvement.
Design and implement web-based SaaS capabilities using C#, .NET, Angular, JavaScript/TypeScript, SQL, and modern web architecture patterns.
Build automated unit, integration, API, contract, and end-to-end tests where appropriate.
Improve CI/CD pipelines, branching and merging strategies, release practices, developer workflows, and containerized delivery with Docker and Kubernetes.
Build secure, resilient, observable Azure services using capabilities such as Key Vault, Application Insights, Service Bus, Application Gateway, Azure SQL, Cosmos DB, and Azure Storage.
Manage direct reports through coaching, feedback, development planning, goal setting, performance management, and talent development while raising engineering standards through mentoring, design reviews, code reviews, reusable patterns, and documentation.
Requirements
Software engineering experience including hands-on delivery of complex, production software systems.
Experience managing direct reports in a software engineering organization, including hiring, coaching, development planning, performance reviews, retention, and performance management.
Deep practical experience using Claude Code or comparable AI coding agents, with the ability to use AI across planning, implementation, testing, debugging, review, documentation, and refactoring.
Strong hands-on experience building production web applications with C#, .NET, Angular, JavaScript/TypeScript, APIs, data models, services, user interfaces, and background processing.
Strong familiarity with Azure, Azure DevOps, Git, CI/CD, automated testing, Docker, Kubernetes, observability, and production operations.
A track record of mentoring engineers, influencing technical direction, improving engineering practices, and communicating trade-offs clearly across product, engineering, architecture, security, and operations stakeholders.
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