Engineering Manager (NOTA)

Overview       The Engineering Manager leads high-performing software engineering teams responsible for delivering secure, scalable, and resilient digital products and platforms. This leader combines strong people leadership with modern technology expertise across full-stack application development, cloud platforms, DevOps, observability, and engineering delivery practices. The Engineering Manager partners closely with Product Management, Architecture, Cybersecurity, Infrastructure, Operations, and Business stakeholders to define technical strategy, execute product roadmaps, and drive engineering excellence. This role is accountable for the successful delivery and operational health of critical business capabilities while fostering a culture of innovation, continuous improvement, accountability, and talent development. The Engineering Manager is expected to champion the responsible adoption of Artificial Intelligence (AI) and Generative AI technologies within engineering teams. This includes identifying opportunities to improve developer productivity, software quality, operational efficiency, customer experiences, and decision-making through AI-enabled solutions. The role partners with Product, Architecture, Data, Risk, and Technology leadership to evaluate and implement AI capabilities consistent with enterprise standards, governance, security, and regulatory requirements. The ideal candidate has experience leading teams building and operating cloud-enabled applications utilizing modern architectures, Azure services, Agile delivery practices, CI/CD automation, and Site Reliability Engineering (SRE) principles. Primary Responsibilities Engineering Leadership & Delivery Lead multiple engineering teams responsible for the design, development, testing, deployment, and support of mission-critical applications and digital products. Establish engineering strategies, roadmaps, and delivery plans aligned to business objectives and technology modernization initiatives. Drive predictable delivery across multiple Agile teams while balancing feature delivery, technical debt reduction, operational stability, and risk mitigation. Promote engineering excellence through modern software development practices, code quality standards, automated testing, peer reviews, and continuous integration/deployment. Technical Leadership Provide technical leadership across full-stack application development, including frontend, backend, APIs, microservices, integration patterns, databases, and cloud-native technologies. Partner with Architecture to define solution designs, modernization strategies, and target-state technology roadmaps. Guide teams in building scalable, secure, resilient, and observable systems leveraging Azure cloud services and platform capabilities. Evaluate emerging technologies, frameworks, and vendor solutions to improve development productivity and business outcomes. Drive adoption of engineering best practices including Infrastructure as Code (IaC), API-first design, event-driven architecture, and reusable platform capabilities. Guide engineering teams in designing and supporting AI-enabled applications and intelligent business capabilities. Collaborate with enterprise architecture and data teams to define patterns for AI, machine learning, and Generative AI integrations. Evaluate tradeoffs related to AI solution architecture, scalability, governance, model risk, security, explainability, and operational support. AI & Innovation Leadership Drive adoption of Artificial Intelligence (AI) and Generative AI capabilities across the software development lifecycle and engineering organization. Identify opportunities to leverage AI tools to improve software development productivity, code quality, testing effectiveness, operational efficiency, and customer outcomes. Promote responsible use of AI technologies aligned with enterprise governance, security, privacy, and compliance standards. Partner with Architecture, Product, Data Engineering, and Business teams to evaluate AI-enabled products, services, and engineering accelerators. Lead experimentation and innovation efforts utilizing emerging technologies including Generative AI, Large Language Models (LLMs), agentic workflows, intelligent automation, and predictive analytics. Establish engineering practices for AI-assisted development including code generation, test automation, documentation generation, knowledge management, and software modernization activities. Evaluate emerging AI platforms, frameworks, and vendor solutions to support business and engineering objectives. Foster AI literacy and continuous learning across engineering teams. Cloud & Platform Engineering Lead the adoption and optimization of Azure cloud technologies and engineering platforms. Partner with infrastructure and platform teams to establish secure, scalable, and compliant cloud environments. Promote automation, self-service engineering capabilities, and platform modernization efforts. Ensure applications leverage appropriate Azure services, monitoring solutions, and operational controls. DevOps, Reliability & Operational Excellence Champion DevOps, CI/CD, observability, and Site Reliability Engineering (SRE) practices. Establish metrics and operational objectives related to availability, reliability, performance, scalability, and customer experience. Lead production readiness reviews, incident management, root cause analysis, and continuous improvement efforts. Ensure applications meet resiliency, disaster recovery, and security requirements. People Leadership Develop engineering talent in emerging technology domains including cloud engineering, AI, automation, platform engineering, and modern software development practices Build, develop, and retain high-performing engineering teams through coaching, mentoring, succession planning, and career development. Foster an inclusive, collaborative, a