Senior Engineering Manager

Accountabilities:

• Lead and develop engineering teams through regular coaching, feedback, performance management, career development, and clear expectations while fostering accountability, autonomy, innovation, and continuous learning.


• Develop senior engineers, technical owners, and emerging leaders by increasing leadership capacity and empowering them to own initiatives from discovery through implementation.


• Support hiring, onboarding, retention, and talent development while identifying capability gaps and partnering with engineering leadership on organizational and workforce planning.


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


• Improve engineering operating practices, team rhythms, planning processes, backlog readiness, delivery tracking, and blocker resolution while avoiding unnecessary process overhead.


• Identify and resolve cross-team dependencies and systemic delivery issues, working with Engineering and Product leadership when challenges extend beyond individual teams.


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


• Communicate progress, risks, challenges, resource requirements, and delivery outcomes clearly and proactively to leadership and cross-functional stakeholders.


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


• Partner with senior and principal engineers to evaluate technical approaches, challenge assumptions, and ensure appropriate ownership of architecture and technical decisions.


• Maintain sufficient hands-on technical engagement to remain credible and provide informed guidance on complex engineering decisions.


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


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


• Establish and monitor SLOs, error budgets, and other reliability measures, taking corrective action when reliability trends deteriorate.


• Provide leadership during major incidents through effective coordination, decision-making, escalation, and stakeholder communication, followed by meaningful postmortems and tracked corrective actions.


• Partner with Product and cross-functional stakeholders to establish clear problem statements, business context, priorities, and success criteria while preserving engineering ownership of solution design.


• Champion effective AI-assisted development practices across solution exploration, technical planning, ticket creation, development, and other workflows while maintaining engineering quality and accountability.


• Enable engineers to participate earlier in discovery, clarify requirements, contribute to solution design, and translate business needs into well-defined technical work.


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

Requirements

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


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


• Have experience leading multiple engineering teams or initiatives involving multiple teams and stakeholders.


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


• Have experience partnering with senior Engineering and Product leadership on organizational priorities, resource requirements, technical tradeoffs, and execution strategy.


• Bring experience owning production services, including on-call operations, SLOs, incident response, and postmortems.


• Be experienced in collaborative Product and Engineering environments where engineers actively participate in discovery, requirements definition, technical solutioning, and delivery.


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


• Possess strong communication and stakeholder management skills, with the ability to create clarity across Engineering, Product, and other cross-functional teams.


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


• Bring strong Java/Kotlin development experience and the ability to provide technical guidance across backend services and microservices.


• Have experience leveraging or leading teams that use AI-assisted software development tools and workflows.


• Recent hands-on coding experience is preferred.


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


• React framework experience is a plus.


• Experience designing and implementing microservice architectures for distributed systems and reliable platforms is a plus.


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

• Annual compensation of $220,000 USD.


• Full-time position with a remote work arrangement.


• Opportunity to lead engineering teams building AI-powered data connectivity solutions.


• Significant scope to influence technical direction, engineering practices, organizational structure, and delivery strategy.


• Opportunity to develop senior engineers and emerging technical leaders while contributing to broader engineering effectiveness.


• Exposure to AI-assisted software development and modern cloud-native engineering practices.

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