Software Engineering Manager

Skills

About the Role

You will lead a team of highly talented full stack developers, responsible for the development and delivery of the self-service tools and experiences behind Norton's public-facing customer support portal. You'll collaborate with product managers, architects, data scientists, and business partners to design, develop, and deliver solutions that meet functional requirements and exceed systems performance expectations. You will champion the responsible integration of AI capabilities into products and engineering workflows, helping your team move faster without sacrificing quality or safety. You'll also handle technical solution review, design documents, functional specifications, hiring, and promote industry best practices, including emerging best practices around AI systems.

Requirements

• BS in Computer Science, Computer Engineering, or equivalent combination of education and experience
• 10+ years of full-time software engineering experience, including hands-on work in backend and/or client-side systems
• 5+ years of Agile development experience, including team leadership or management
• Demonstrated experience working with or shipping AI-powered features in production environments
• Experience with RESTful API design and microservices architecture
• Working knowledge of source code control systems and release management (Jira, Git/GitHub, and associated workflows)
• Strong communication and collaboration skills; ability to influence without authority across engineering, product, and data science teams
• Demonstrated passion for high-quality solutions and engineering excellence
• Experience with CI/CD pipelines and DevOps practice
• Experience with Kubernetes, Azure, AWS, or Google Cloud
• Experience with NoSQL technologies (MongoDB, DynamoDB, Redis)
• Experience with Ruby, Java, or React
• Experience with self-service support technologies: help-center search, knowledge bases, or web chatbot/virtual-agent platforms

Responsibilities

• Coordinate schedules and milestones with cross-functional stakeholders and clients
• Assign, review, and guide the work of software engineers; monitor team capability, capacity, progress, and delivery across sprint cycles
• Analyze development workflow, establish priorities, develop standards, and set deadlines; proactively identify and resolve performance breakdowns
• Provide candid, constructive feedback; maintain high visibility into project health for senior leadership and stakeholders
• Identify, introduce, and champion AI-assisted developer tooling such as code generation, code review assistants, and automated testing
• Uphold principles of fairness, transparency, and safety when evaluating, shipping, and monitoring AI systems; define guardrails and human-in-the-loop checkpoints
• Guide the team's use of large language models and prompt engineering; ensure model outputs are evaluated for quality, safety, and reliability
• Oversee the integration of LLM APIs into production systems
• Define evaluation frameworks for AI features, including metrics and regression testing
• Anticipate and mitigate AI risks such as hallucination, data privacy, model drift, adversarial inputs, and regulatory considerations