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.
Description:
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.
