Top Tech Jobs & Startup Jobs in San Francisco, CA

Develop and optimize AI compilers and code generation for new hardware, using LLVM/MLIR, Torch Dynamo, and Triton. Implement compiler features and optimizations in C++ and Python, improve AI workload performance, design programming abstractions, collaborate with hardware and ML teams, and plan and deliver engineering solutions.

Design and scale ultra-low-latency Ethernet and InfiniBand fabrics for hyperscale AI training. Engineer ROCE transport, congestion control (ECN/WRED/DCTCP), telemetry, routing, and observability; bring up clusters, benchmark AI workloads, debug performance, and collaborate with silicon and datacenter partners to deploy large-scale AI infrastructure.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers to translate requirements into technical designs, apply engineering best practices (CI/CD, testing, observability), and deliver end-to-end solutions. Lead technical workstreams, collaborate across disciplines, and apply AI/LLM techniques to production deployments while ensuring security, quality, and maintainability.

Lead and deliver complex, cross-functional engineering programs embedded with customer teams. Define customer scenarios, serve as Product Owner, create roadmaps, coordinate stakeholders, track schedules, drive implementation and governance, validate use cases, write test cases, and support customer engagements to deploy cloud and AI solutions.

Lead and scale a portfolio of forward-deployed engineering programs: design program strategy, set operating cadences, align stakeholders, track portfolio-level success metrics, quantify ROI, drive data-informed decisions, and ensure sustained customer impact across teams and regions.

Lead data science engagements with customers to acquire and prepare data, build and evaluate scalable models, implement production-ready solutions, and define business and solution strategy while collaborating with engineers and product teams.

Lead commercial strategy and deal execution for Microsoft customers: craft and negotiate compliant, profitable commercial solutions; optimize price and non-price concessions; define complex negotiation strategies; build trusted relationships with customers, partners, and internal teams; manage account commercial plans, anticipate renewals, and drive quota, consumption, and compliant deal outcomes.

Drive technical pre-sales for data security solutions: run demos, PoCs, hackathons, and architecture workshops; design secure, scalable architectures using Microsoft platforms; advise on data governance and AI security; resolve technical blockers and influence product and deployment decisions.

Lead investigation and analysis of large-scale distributed storage systems, identify bottlenecks and load concentration, design algorithms to improve availability and efficiency, debug faults across stacks, collaborate cross-team, mentor engineers, act as a DRI and on-call responder, and improve observability and performance for Azure Managed Disks at hyperscale.

Own end-to-end design, launch, and operational execution of Unified Enterprise service offerings. Drive product strategy, GTM, pricing/SKU architecture, cross-functional enablement, and embed AI capabilities while partnering with Finance, Sales, Delivery, and engineering to scale global customer success.