$ cat jobs/staff-software-engineer-fortive-62d927fb4db1.json
Staff Software Engineer
We are looking for an experienced Tech Lead (Staff Software Engineer) to lead a high-impact engineering team building scalable, cloud-native applications with modern DevOps practices. You will own technical strategy, architecture decisions, and delivery while mentoring engineers and driving innovation in both traditional software engineering and AI-powered solutions. This is a hands-on leadership role — you will code, design systems, and set the technical direction for critical initiatives. Key Responsibilities Lead and mentor a team of software engineers, setting technical standards and best practices Architect and deliver scalable cloud systems using Infrastructure as Code (Terraform) Design and implement full-stack features leveraging TypeScript (Node.js/React or similar) and C# (.NET) Own end-to-end DevOps pipelines — CI/CD, monitoring, infrastructure automation, and reliability Integrate AI engineering capabilities into products (LLM integration, generative AI features, AI agents, RAG pipelines, etc.) Collaborate with product and cross-functional teams to translate business needs into technical solutions Conduct code reviews, architectural reviews, and drive continuous improvement in code quality, performance, and security Champion cloud best practices, cost optimization, and platform modernization initiatives Required Qualifications 8+ years of professional software engineering experience (3+ years in a technical leadership or Staff+ role) Strong expertise in Cloud platforms (AWS and Azure — multi-cloud experience a plus) Advanced proficiency with Terraform for infrastructure provisioning and management at scale Deep hands-on experience with TypeScript (Node.js ecosystem, TypeScript best practices, modern frameworks) Strong command of C# and the .NET ecosystem (ASP.NET Core, microservices, APIs) Proven DevOps expertise: GitHub Actions / Jenkins, Docker/Kubernetes, monitoring, and infrastructure automation Solid understanding of AI engineering concepts and prac
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