Principal AI Platform Engineer
Location: Onsite
Primary is San Leandro, CA, Secondary – Pittsburgh, PA, Scottsdale Arizona,

Top Skills:
Applied AI | Cloud Platforms | Industrial Software | Multicloud Engineering

JD:
The Opportunity We are seeking a Principal AI Platform Engineer to design and deliver enterprise-grade AI and cloud platform capabilities. You will combine deep hands-on engineering with technical leadership across applied AI, distributed systems, multicloud architecture, industrial data, and developer productivity. You will collaborate with Product, R&D, Architecture, Cloud Operations, and customer-facing teams to turn complex needs into secure, scalable, reusable, and production-ready solutions. What You Will Do • Design, build, deploy, and operate AI-enabled services, APIs, connectors, libraries, automations, and reusable platform assets. • Apply Generative AI, LLMs, RAG, agents, orchestration, vector search, evaluation, grounding, safety, monitoring, and cost controls to production use cases. • Architect cloud-native services using C#, .NET, ASP.NET Core, REST APIs, microservices, containers, Kubernetes, serverless computing, event-driven patterns, and secure service design. • Lead or contribute to Azure and AWS platform engineering across identity, data, messaging, API management, infrastructure-as-code, CI/CD, observability, and operational readiness. • Design and execute cloud migrations, including Azure-to-AWS scenarios, with attention to portability, provider dependencies, data, networking, resilience, cost, cutover, and rollback. • Solve production challenges involving reliability, latency, security, compliance, performance, scalability, and supportability using telemetry, profiling, benchmarks, and load testing. • Build solutions for industrial and operational data, including time-series data, historians, SCADA/OT, MES, ERP/EAM integration, digital twins, and edge-to-cloud interoperability. • Use AI-assisted engineering for codebase analysis, modernization, refactoring, migration, performance investigation, and test generation, with measurable validation and human review. Page 1 Principal AI Platform Engineer How You Will Lead • Influence architecture and engineering decisions across complex product initiatives. • Coach engineers and architects, strengthen engineering practices, and raise quality without relying on direct people-management authority. • Translate recurring customer needs, implementation friction, and product gaps into reusable assets, reference implementations, and actionable Product and R&D recommendations. • Communicate complex technical concepts clearly to engineers, architects, customers, Product, R&D, and senior stakeholders. What You Bring • Typically 10-14 years of relevant experience, or equivalent demonstrated capability, in software engineering, applied AI, cloud or platform engineering, industrial software, or complex product engineering. • Recognized expertise in applied AI, supported by substantial hands-on experience in cloud-native software, platform engineering, or distributed systems. • Deep practical experience with modern backend engineering, preferably C#, .NET, ASP.NET Core, APIs, microservices, containers, observability, and secure design. • Advanced experience with Azure and AWS across compute, containers or Kubernetes, serverless, databases, storage, messaging, identity, secrets, API management, monitoring, infrastructure-as-code, and CI/CD. • Experience designing production AI systems using LLMs, RAG, agents, vector search, evaluation, grounding, safety, latency, cost, and monitoring practices. • Experience with cloud migration and multicloud portability, including provider-specific dependencies, identity, networking, data movement, resilience, phased cutover, and rollback. • Strong understanding of industrial and operational environments, including time-series data, SCADA/OT, historians, MES, ERP/EAM integration, digital twins, and edge/cloud interoperability. • Strong engineering judgment across architecture, coding, testing, security, observability, deployment, release readiness, maintainability, versioning, documentation, and operational handover. Highly Desirable • Experience designing, evaluating, and operating agentic systems that automate SDLC activities such as requirements analysis, implementation, code review, test generation and execution, dependency upgrades, and release preparation. • Experience integrating agents with source control, CI/CD, and engineering tools using scoped permissions, human approval gates, auditable actions, and safeguards for proprietary code and credentials. • Experience operating AI workloads in regulated, high-availability, industrial, or mission-critical environments. What Success Looks Like You deliver secure, production-ready AI capabilities and reusable engineering assets; improve cloud portability and operational readiness; and demonstrate measurable gains in engineering productivity, software performance, reliability, and customer value. This role is designed for a principal-level technical leader who remains meaningfully hands-on. It is not primarily a people-management position.