Top Engineering Jobs in San Francisco, CA

Designs and leads customer-facing cloud and AI application engagements on Azure, including architecture, proofs of concept, modernization, production readiness, and operational optimization. The role focuses on Azure Logic Apps, AI Foundry, AKS, App Service, APIM, GitHub, containers, and DevOps. Responsibilities include workshops, technical delivery oversight, reusable intellectual property, customer success planning, escalation support, application migration, security, resiliency, mentoring, and influencing product improvements.

Lead design and implement scalable Azure full-stack solutions for Microsoft Skilling platforms. Build CI/CD, automation, observability, and Copilot/GenAI features; improve test automation and reliability; mentor engineers and coordinate cross-team dependencies to deliver secure, high-quality services at enterprise scale.

Design, develop, test, and operate scalable Azure networking software and automation platforms. Automate device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Build AI-powered agents and data-driven tools for troubleshooting, root-cause analysis, and engineering productivity. Develop reliable distributed systems with observability, diagnostics, recovery, and scalability while collaborating across engineering teams and driving architecture, code quality, testing, monitoring, and continuous improvement.

Design and implement compiler, code-generation, JIT-compilation, system, and runtime components for deploying applications to AI accelerator devices. Analyze and transform LLVM IR, develop optimized systems-level software, collaborate with hardware and machine-learning teams, and plan deliverables while contributing to robust engineering practices.

Design, implement, and debug low-level software for Azure HPC/AI VMs, focusing on hardware/software interactions, device virtualization, and GPU workload performance. Drive architecture, collaborate with partners, own reliability as an on-call DRI, and develop operational playbooks to improve stability and performance.

Lead and develop Site Reliability Engineering teams responsible for Microsoft Substrate services in regulated environments. Own reliability, availability, incident response, disaster recovery, SLOs, operational metrics, and compliance. Drive automation, self-healing systems, observability, engineering-led operational excellence, and durable post-incident improvements. Partner across engineering, product, security, infrastructure, and compliance teams while shaping reliability strategy and mentoring senior and principal engineers.

Lead design and delivery of production-ready cloud and AI systems while embedding with customer teams. Own end-to-end architecture, secure coding, CI/CD, testing, observability, and operational excellence. Mentor engineers, drive adoption, create reusable assets, and coordinate complex deliveries to achieve measurable business outcomes.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers and stakeholders to translate needs into technical designs, drive engineering best practices (CI/CD, automated testing, observability), deliver end-to-end solutions, and lead technical workstreams. Apply AI/LLM techniques, reusable components, and a security-first mindset while collaborating across disciplines.

Lead architecture and roadmap for Azure PostgreSQL systems; design and review extensible, maintainable code; prototype and implement database engine features (query processing, transaction logging, storage, versioning, IO, scale-out); contribute to open-source PostgreSQL/Linux; operate production services including rotational on-call support.

Lead technical authority for InfiniBand and GPU interconnect fabric operations in hyperscale AI/HPC environments. Own incident leadership, deep multi-layer debugging across hardware/firmware/drivers/OS, define failure models, operational standards, and build automation, telemetry, and tooling to improve reliability and observability at fleet scale.