Software Engineering Manager
Hybrid, 3 days onsite
Role Overview
We are looking for a hands-on Software Engineering Manager to lead engineers working on the team.
This role is for an engineering manager who stays close to the technology. You should be comfortable leading people, reviewing technical designs, reasoning through code-level issues, guiding performance and reliability tradeoffs, and helping the team deliver high-quality software in an Agile environment. You will partner with Product Management, architects, peer engineering teams, QA, and customer-facing teams to deliver capabilities that help enterprise customers manage, protect, and activate unstructured file data at global scale.
This is not a director-level or delivery-only management role. The right candidate is a people manager and technical leader who can coach engineers while remaining close to the code, systems behavior, and customer impact of the work.
Level & Scope Definition
You will own execution and people leadership for a software engineering team within a defined product area. You will guide day-to-day technical decisions, help shape implementation plans, support roadmap tradeoffs, and ensure the team delivers reliable, performant, maintainable software. You will not be expected to own an entire engineering portfolio, but you will be expected to influence quality, architecture, engineering practices, and delivery outcomes within the Data Path domain.
Responsibilities
- Lead, coach, and manage a team of software engineers, including regular feedback, performance management, career development, and team health.
- Stay close to technical execution through design reviews, code-level discussions, debugging, performance analysis, and production issue review.
- Oversee delivery of Data Path features, fixes, and releases for Linux-based systems
- Partner with Product Management, architects, and engineering peers to clarify requirements, evaluate tradeoffs, and plan high-quality execution.
- Drive engineering practices that improve reliability, performance, maintainability, observability, and release confidence.
- Help the team respond effectively to critical customer escalations, including root-cause analysis and durable corrective actions.
- Use data, metrics, and engineering judgment to identify process, quality, and technical improvements.
- Apply AI-assisted engineering workflows responsibly where useful, such as test generation, code review support, debugging, documentation, or operational analysis, while validating outputs with strong technical judgment.
- Build a positive, accountable team culture grounded in ownership, collaboration, curiosity, and continuous improvement.
Expected Outcomes and Impact
In the first 6–12 months, this manager should improve team execution, raise technical quality, strengthen performance and reliability practices, and help deliver Data Path work that supports enterprise-scale customer usage. Success will be measured by team health, delivery predictability, product quality, technical judgment, and the ability to help engineers solve complex systems problems.
Qualifications
Must-Have
- 10+ years of software engineering or systems development experience.
- 5+ years as an engineering manager, technical lead, or team lead in an Agile product development environment.
- Strong hands-on technical background in storage systems, distributed systems, databases, cloud infrastructure, or similar systems-level software.
- Experience designing, building, debugging, or supporting software that runs on Linux.
- Practical experience with system-level performance analysis, reliability improvement, and troubleshooting.
- Knowledge of networking concepts and application protocols.
- Experience supporting critical customer escalations or production-impacting engineering issues.
- Proven ability to coach engineers, provide performance feedback, and lead technical delivery.
- Strong written and verbal communication skills.
Preferred
- Experience with file systems, object storage, caching, synchronization, data path performance, or edge/cloud storage architectures.
- Experience with C, C++, Go, Python, or similar systems-oriented languages.
- Experience with cloud platforms, observability tools, release management, or distributed team execution.
- Experience improving engineering workflows using AI-assisted tools while maintaining quality, security, and validation standards.
Ideal
- Experience leading teams that build enterprise infrastructure, storage, data protection, or high-scale SaaS platforms.
- Track record of managing engineers while remaining hands-on in architecture, design, debugging, and code-level tradeoffs.
- Experience in a high-growth SaaS or private-equity-backed software environment.
