Sr SW Engineering Manager

Senior Engineering Manager

Job Summary

Lead engineering teams building AI-powered data connectivity solutions. In this role, you will combine strong people leadership, technical judgment, and execution to help engineering teams deliver high-quality software quickly and effectively.

As a Senior Engineering Manager, you will provide leadership to engineering teams, owning execution and delivery while helping establish the operating practices, technical direction, and organizational clarity needed for teams to perform effectively. You will ensure priorities are clear, work moves forward, dependencies and blockers are addressed, and commitments remain on track while partnering with Engineering and Product leadership on capacity, priorities, risks, and longer-term planning.

You will also help foster a shift-left engineering model in which engineers engage earlier in discovery and solution definition. Rather than simply executing against fully prescribed requirements, engineers will partner with Product and other stakeholders to understand customer and business problems, shape technical solutions, and translate those solutions into actionable technical work. AI is used throughout the process, both in the product we ship and in how we build it, to support solution exploration, planning, and development without lowering the technical quality bar.

You will balance this execution with strong people leadership, developing engineers through regular feedback, coaching, career development, and clear performance expectations. You will create an environment of accountability, autonomy, collaboration, and continuous learning while ensuring the engineering team's work remains aligned with broader Product and Engineering priorities.

Responsibilities:

Responsibilities include but are not limited to:

People Leadership

• Lead and develop engineering teams, providing regular coaching, feedback, and performance management while fostering a culture of accountability and innovation.

• Develop senior engineers, technical owners, and emerging leaders, increasing the leadership capacity within the organization.

• Empower senior engineers and technical owners to take ownership of initiatives, rapidly prototype and validate solutions, make sound technical decisions, and drive work from discovery through implementation.

• Hire, onboard, retain, and develop strong engineering talent while identifying capability gaps and partnering with Engineering leadership on organizational and workforce needs.

• Partner with Engineering leadership on team structure, capacity planning, resource allocation, and talent development across the organization.

Execution and Delivery

• Own execution and delivery across assigned engineering teams or a broader engineering area, ensuring priorities, ownership, dependencies, risks, and commitments are clearly understood and actively managed.

• Continuously improve operating practices that enable predictable delivery, appropriate accountability, and visibility across teams without creating unnecessary process overhead.

• Ensure effective team-level operating rhythms, including planning, backlog readiness, delivery tracking, and blocker resolution, while developing leaders within teams who can increasingly drive day-to-day execution.

• Identify and resolve cross-team dependencies and systemic delivery issues, partnering with other Engineering leaders and Product leaders when challenges extend beyond the immediate team.

• Use streamlined workflows, automated reporting, and meaningful engineering and delivery metrics to identify trends, improve execution, and inform decisions.

• Communicate progress, risks, challenges, resource needs, and delivery outcomes clearly and proactively to Engineering leadership and other stakeholders.

Technical Leadership

• Provide strong technical leadership and judgment across teams, ensuring engineering decisions align with architectural direction, quality expectations, reliability standards, and broader technical strategy.

• Partner closely with senior and principal-level engineers to evaluate technical approaches, challenge assumptions, and ensure appropriate ownership of architecture and technical decision-making.

• Stay technically credible by maintaining enough hands-on technical engagement to effectively guide the team and make informed technical decisions.

• Identify recurring technical challenges across teams and help drive broader improvements to engineering practices, architecture, tooling, and ways of working.

Operational Ownership

• Ensure effective operational ownership across assigned teams, including sustainable on-call practices, appropriate staffing, and clear accountability for production systems.

• Ensure teams establish and effectively use SLOs, error budgets, and other reliability measures and take action when trends move in the wrong direction.

• Provide leadership during major incidents, ensuring effective coordination, decision-making, escalation, and stakeholder communication through resolution.

• Drive operational excellence across teams through leading effective postmortems and ensuring meaningful action items are tracked through closure.

• Identify recurring operational patterns and partner across Engineering to address root causes and improve reliability at an organizational level.

Discovery & AI-Assisted Development

• Partner closely with Product and cross-functional stakeholders to ensure teams have clear problem statements, business context, priorities, and success criteria while preserving appropriate engineering ownership of solution design and implementation.

• Champion effective use of AI-assisted development practices, helping teams leverage AI appropriately for solution exploration, technical planning, ticket creation, development, and other workflows while maintaining engineering quality and accountability.

• Help establish effective Product and Engineering working practices across teams, resolving areas of unclear ownership or ineffective handoffs.

• Enable engineers to participate earlier in discovery, clarify problem statements, contribute to requirements, develop technical solutions, and translate those solutions into well-defined technical work.

• Identify opportunities to use AI, automation, and improved engineering practices to increase developer productivity and organizational effectiveness.

Qualifications

Must Haves:

• 8+ years of software engineering experience, including hands-on experience in enterprise or SaaS environments with a strong focus on technical competency and innovation.

• 4+ years of engineering management and/or people management experience with demonstrated success leading, coaching, and developing engineering teams.

• Experience leading multiple engineering teams or initiatives spanning multiple engineering teams and stakeholders.

• Proven ownership of team execution and delivery, including planning, prioritization, dependency management, risk identification, and continuous improvement of development workflows.

• Experience partnering with senior Engineering and Product leadership on organizational priorities, resource needs, technical tradeoffs, and execution strategy.

• Experience owning production services, including on-call, SLOs, incident response, and postmortems.

• Experience working in highly collaborative Product and Engineering environments where engineers participate actively in discovery, requirements definition, technical solutioning, and delivery.

• Strong technical judgment with the ability to guide design decisions, challenge assumptions, and empower senior and lead engineers to own technical initiatives.

• Strong communication and stakeholder management skills, with the ability to create clarity across engineering, product, and other cross-functional teams.

• Experience with cloud platform management and architecture, preferably Azure, supporting scalable, high-performance systems and cloud-native deployments.

• Strong Java/Kotlin development experience, with the ability to provide technical guidance across backend services and microservices development.

• Experience leveraging or leading teams that leverage AI-assisted software development tools and workflows.

• Recent hands-on coding experience is preferred.

• Kubernetes experience and familiarity with container orchestration and deployment is a plus.

• React framework experience is a plus.

• Experience designing and implementing microservice architectures supporting distributed systems and system reliability is a plus.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.