At Siemens, we help organizations transform maintenance and operations through connected insights, AI-powered technology, and intelligent asset management solutions. Our software enables customers to manage the full lifecycle of assets, facilities, and infrastructure while improving efficiency, reducing risk, and optimizing long-term investments. By connecting data, people, and processes, we empower organizations to make smarter decisions, improve asset performance, and achieve more resilient operations.
Siemens is looking for a Senior Manager of Engineering to provide strong technical leadership, vision, and mentoring across multiple onshore and offshore software engineering teams. This is a high-impact leadership role responsible for day-to-day management of projects and sprints, driving delivery of key business objectives, and building a world-class engineering culture. You will lead teams that are actively accepting AI-augmented engineering — from AI-assisted coding and automated code review to agentic development pipelines that fundamentally change how software gets built. We are looking for a leader who not only understands these shifts but champions them, helping their teams adapt, experiment, and operate at a higher level of output and quality.
YOU’LL MAKE AN IMPACT BY:
- Lead, develop, and grow multiple software engineering teams (10–20+ engineers) across onshore and offshore locations — owning hiring, performance management, career development, and team health.
- Coordinate and direct project and sprint execution; build detailed delivery plans, manage dependencies, remove blockers, and ensure commitments are met within scope, budget, and quality targets.
- Champion AI-augmented engineering practices across your teams — driving adoption of AI coding assistants, agentic development workflows, and LLM-powered tooling that accelerates the SDLC and raises the quality bar.
- Partner with Staff and Principal Engineers to guide architecture decisions, uphold development standards, and ensure technology choices support current product needs and long-term platform direction.
- Collaborate with Product Management to provide technical insight on feature/schedule/cost trade-offs, translate business priorities into engineering roadmaps, and actively shape what gets built and when.
- Drive a metrics-informed engineering culture — using DORA metrics, cycle time, defect rates, AI productivity signals, and team health data to identify improvement opportunities and demonstrate progress.
- Identify strategic opportunities and risks in emerging technologies — particularly in AI/ML and agentic systems — and develop plans that keep our products and engineering practices ahead of the curve.
THIS IS HOW YOU’LL WIN US OVER:
- 10+ years of experience in the software industry, with 3+ years in engineering management, including direct people management (hiring, performance, career growth).
- Proven track record leading and scaling mid-to-large engineering teams (10+ people) in a SaaS or service-oriented product environment.
- Deep experience with agile delivery at scale — Scrum, Kanban, or SAFe — including managing multiple squads or workstreams simultaneously.
- Strong technical foundation: hands-on background in software engineering with experience designing and building secure, scalable, cloud-native or microservices-based platforms.
- Demonstrated ability to communicate clearly and influence effectively across engineering teams, product managers, senior leadership, and business stakeholders.
- Experience using engineering metrics and data-driven analysis to guide decision-making, prioritize investments, and improve team delivery.
YOU’LL THRIVE EVEN MORE IF YOU ALSO BRING
- Active champion of AI-augmented engineering: you have introduced or scaled AI coding assistants (GitHub Copilot, Cursor, Claude Code, or equivalent) across a team and can articulate the productivity and quality impact.
- Hands-on familiarity with agentic development concepts — LLM-powered pipelines that automate multi-step SDLC tasks such as story enrichment, code generation, test writing, security review, and PR summarization — and experience evaluating, adopting, or building such systems in an engineering org.
- Ability to set a responsible AI policy for your teams: establishing human-in-the-loop checkpoints, output quality standards, and guardrails so that agentic workflows accelerate delivery without compromising reliability or security.
- Cloud platform expertise — AWS, Azure, or GCP — including containers, Kubernetes, and modern CI/CD practices.
- Experience managing distributed, globally-distributed engineering teams across time zones and cultures.
- Certifications in cloud platforms, AI/ML, agile methodologies, or engineering leadership programs.
- Prior experience in a high-growth SaaS company scaling from early-stage to enterprise-grade delivery.
At Siemens, you’ll have the opportunity to grow your career while helping organizations operate smarter, safer, and more sustainably. We develop a culture of innovation, collaboration, and continuous learning, where leaders are empowered to make a difference every day. If you’re excited about building high-performing engineering teams, driving AI-native ways of working, and shaping the future of intelligent asset management, we encourage you to apply.
