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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Leader, Software Engineering (Hybrid) - **Company:** Cisco Systems, Inc. - **Location:** Richardson, TX, United States - **Experience:** Expert - **Salary:** $177,600.0 - $257,400.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Computing, PCI Data Security Standards, Reliability Engineering, Azure Machine Learning, Software Deployment, Software Engineering, Cisco WebEx, AI Infrastructure, Cloud Platform System, Large Language Models, AI Platforms, Information Technology - **Published:** September 1, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88200866/1 ## About the Role * Bachelor's degree in Computer Science, Engineering, or a related field with 15+ years of relevant experience, or Master's degree with 12+ years. * Minimum of 4 years of direct supervisory or management experience leading software or platform engineering teams. * Experience directing platform, infrastructure, or shared-services engineering supporting multiple downstream product teams. * Experience leading large-scale, complex platform initiatives from technical requirements through production deployment. * Experience defining and implementing technical standards for design, security, and testing in cloud-based environments (FedRAMP, PCI-DSS, or comparable regulated environments strongly preferred)., * Hands-on familiarity with AI/ML platform concerns such as LLM inference, model routing, cost and capacity management across hyperscalers (AWS Bedrock, Azure OpenAI/Foundry, OpenAI). * Strong leadership presence with a track record of mentoring senior engineers and building high-performing platform teams. * Excellent communication skills, including presenting platform strategy, compliance posture, and technical trade-offs to executive stakeholders and partner teams. * Demonstrated ability to build consensus across service owners, product, SRE, and security/compliance stakeholders. * Strategic mindset focused on continuous improvement: identifying architectural, tooling, and process efficiencies that compound across the org. * Experience with Agile or similar methodologies in a fast-paced, global engineering environment. ## Description The CollabAI Platform team is the foundation that powers AI capabilities across Webex. LLM access, guardrails, model routing across OpenAI / Azure Foundry / AWS Bedrock, and the shared services that CollabAI product teams and downstream Webex features depend on. We operate at the intersection of AI infrastructure, cloud platform engineering, and security/compliance, and we're responsible for making sure every AI-powered feature in the product portfolio has a reliable, cost-efficient, and compliant path to production, including in regulated environments like FedRAMP. We partner closely with product engineering, SRE, security, and our hyperscaler partners to deliver a platform that lets the rest of the org move fast without compromising on safety, quality, or cost. Your Impact Lead the CollabAI Platform engineering team through the full design, development, and rollout lifecycle of foundational AI platform services as the team transitions to a broader scope of ownership. Drive platform posture across multiple AI compliance programs, partnering with security and pen-test teams on scoped assessments and remediation. Establish rigorous engineering standards for design reviews, security, observability, and quality, such as load/latency SLAs, and incident response for platform-impacting events. Manage cross-team commitments and trade-offs, aligning platform roadmap and resource allocation with product priorities across CollabAI, Meetings, Messaging, and Contact Center. Partner cross-functionally with product management, SRE, security/compliance, hyperscaler account teams (AWS, Azure, OpenAI), and consuming product teams to translate stakeholder needs into platform decisions. Optimize platform architecture and workflows to improve development velocity, reduce cost per inference, and ensure the platform scales with growing AI adoption across the BU. ## Related Videos - [Platform Engineering vs. DevOps Why not both?](https://www.wearedevelopers.com/videos/885-platform-engineering-vs-devops-why-not-both) - [Developer Tools for Microsoft Azure](https://www.wearedevelopers.com/videos/450-developer-tools-for-microsoft-azure) - [This App Reached 10,000 Users in One Week. 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