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About the Role
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 role 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, 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.
Responsibilities
- 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.
- 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.
- 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.
- 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.
- 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.
- 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, and innovative engineering culture.
- Set performance expectations, provide continuous feedback, and support employee growth and advancement.
- Recruit, onboard, and develop engineering talent while aligning staffing plans to strategic priorities.
- Serve as a trusted advisor and technology partner to business leaders and senior technology leadership.
- Translate business needs into technical capabilities and execution plans.
- Communicate technology strategy, delivery progress, risks, and investment opportunities to executive stakeholders.
- Build strong partnerships across Engineering, Product, Architecture, Risk, Compliance, and Operations teams.
- Ensure adherence to enterprise architecture standards, cybersecurity policies, regulatory requirements, and risk management practices.
- Design and maintain effective controls within the software delivery lifecycle.
- Identify, assess, and escalate technology risks appropriately.
- Support internal audits, regulatory reviews, and remediation activities.
- Builds and retains exceptional engineering talent.
- Delivers business outcomes through modern technology platforms.
- Balances speed, quality, reliability, and risk.
- Leads cloud adoption and modernization efforts.
- Drives engineering excellence through automation and measurement.
- Creates a culture of ownership, innovation, and continuous improvement.
- Operates as both a people leader and technology leader.
- Partners effectively with Product, Architecture, and Business stakeholders to deliver measurable customer value.
- Accelerates delivery and operational excellence through effective use of AI-powered engineering tools and automation.
- Identifies practical AI use cases that improve customer experience, engineering productivity, quality, risk management, and business outcomes.
- Builds a culture of innovation where teams responsibly adopt emerging technologies while maintaining strong governance and engineering discipline.
- Helps transform engineering organizations to leverage cloud, automation, analytics, and AI as competitive advantages.
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Technology, or related field, or equivalent combination of education and experience.
- 10+ years of software engineering experience, including hands-on design and development experience.
- 5+ years of people leadership experience managing engineering teams.
- Experience leading engineering teams utilizing modern software development tools, automation platforms, and AI-assisted engineering practices.
- Strong understanding of current technology trends including cloud computing, AI, software automation, and digital transformation.
- Demonstrated ability to lead technology modernization and innovation initiatives.
- Experience leading teams delivering full-stack applications utilizing modern web, API, integration, and backend technologies.
- Experience with Azure cloud platforms and cloud-native engineering practices.
- Strong understanding of software architecture, distributed systems, and application modernization.
- Experience implementing CI/CD pipelines, automation, DevOps, and Agile delivery practices.
- Experience supporting highly available, customer-facing, and mission-critical applications.
- Strong understanding of SDLC, security practices, risk management, and regulatory requirements.
- Demonstrated ability to lead large-scale technology initiatives and organizational change.
- Excellent communication, stakeholder management, and executive presentation skills.
- Master's degree in Computer Science, Engineering, Business, or related field.
- Experience leading digital transformation or cloud modernization programs.
- Experience with Azure services including App Services, AKS/Kubernetes, Azure DevOps, Azure Functions, API Management, Event Hub, Service Bus, Storage, Key Vault, and Monitoring/Observability platforms.
- Experience building and managing engineering organizations within Agile and product operating models.
- Knowledge of Site Reliability Engineering (SRE), observability, performance engineering, and operational readiness practices.
- Experience with Infrastructure as Code and cloud automation technologies.
- Experience in financial services, fintech, digital banking, or highly regulated environments.
- Proven track record developing engineering talent and building high-performing teams.
- Experience managing multiple concurrent product teams and large technology investment portfolios.
- Strong understanding of modern engineering metrics, including deployment frequency, lead time, change failure rate, availability, and predictability.
Skills
- Full-stack application development
- Cloud platforms
- DevOps
- Observability
- Engineering delivery practices
- Agile delivery practices
- CI/CD automation
- Site Reliability Engineering (SRE)
- Azure services
- Modern architectures
- Artificial Intelligence (AI)
- Generative AI
- Frontend development
- Backend development
- APIs
- Microservices
- Integration patterns
- Databases
- Cloud-native technologies
- Infrastructure as Code (IaC)
- API-first design
- Event-driven architecture
- Large Language Models (LLMs)
- Agentic workflows
- Intelligent automation
- Predictive analytics
- AI-assisted development
- Code generation
- Test automation
- Documentation generation
- Knowledge management
- Software modernization
- Azure cloud technologies
- Engineering platforms
- Automation
- Self-service engineering
- Platform modernization
- Azure services
- Monitoring solutions
- Operational controls
- DevOps
- CI/CD
- Observability
- Site Reliability Engineering (SRE)
- Metrics
- Operational objectives
- Availability
- Reliability
- Performance
- Scalability
- Customer experience
- Production readiness reviews
- Incident management
- Root cause analysis
- Continuous improvement
- Resiliency
- Disaster recovery
- Security requirements
- Cloud engineering
- Automation
- Platform engineering
- Modern software development practices
- Coaching
- Mentoring
- Succession planning
- Career development
- Inclusive culture
- Collaborative culture
- Innovative culture
- Performance expectations
- Continuous feedback
- Employee growth
- Employee advancement
- Recruiting
- Onboarding
- Talent development
- Staffing plans
- Strategic priorities
- Stakeholder management
- Executive presentation
- Enterprise architecture standards
- Cybersecurity policies
- Regulatory requirements
- Risk management practices
- Software delivery lifecycle
- Technology risks
- Internal audits
- Regulatory reviews
- Remediation activities
- Deployment frequency
- Lead time
- Change failure rate
- Availability
- Predictability
Location
- Buffalo, New York, United States of America
Work Type
- Full-time
Experience Level
- 10+ years of software engineering experience
- 5+ years of people leadership experience
Education Level
- Bachelor's degree in Computer Science, Engineering, Information Technology, or related field, or equivalent combination of education and experience.
- Master's degree in Computer Science, Engineering, Business, or related field.
Salary/Compensations
- $139,700.00 - $232,900.00 Annual (USD)
About the Company
- M&T Bank is committed to fair, competitive, and market-informed pay for our employees.