Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead product strategy, roadmap, and delivery for AI-native security experiences. Partner with engineering, security research, design, and data science teams to translate emerging technologies into customer value. Establish operational readiness practices covering release governance, risk management, quality reviews, incident learning, executive readiness, onboarding, adoption, and partner success. Drive complex cross-organizational programs and ensure scalable, reliable launches and measurable customer outcomes.

Develop and optimize GPU kernels, compilers, runtimes, and distributed inference systems for large language model serving. Improve latency, throughput, reliability, and hardware efficiency through profiling and low-level performance optimization. Integrate scalable improvements into production systems, collaborate across model, infrastructure, compiler, and hardware teams, and mentor engineers. Principal-level contributors additionally lead cross-stack initiatives and create reusable performance capabilities across models and hardware generations.

Leads architecture and hands-on development for AI frameworks, performance systems, benchmarking, and developer tools. Investigates issues across models, compilers, runtimes, services, and accelerator hardware; improves model onboarding, runtime performance, reliability, hardware utilization, and Azure efficiency. Establishes scalable measurement and observability capabilities, influences cross-team technical strategy, delivers production solutions, and mentors engineers while advancing engineering quality and maintainability.

Drive enterprise cybersecurity sales by identifying customer needs, building stakeholder relationships, developing solution strategies, and closing security opportunities. Manage technical, business, and partner resources to deliver customer value. Serve as a security subject matter expert, communicate Microsoft Cloud, AI, automation, compliance, identity, and Zero Trust capabilities, conduct forecasting and competitive analysis, and support account planning and digital transformation initiatives.

Lead cross-functional initiatives for Azure Capacity Management by improving operational processes, automation, reporting, governance, and decision-making. Partner with Engineering, Finance, Product, and Business Operations to address ambiguous business needs, coordinate strategic programs, reduce manual effort, and develop scalable operating mechanisms that improve execution and organizational effectiveness.

Leads cross-functional technical programs for Azure’s hardware fleet lifecycle. Develops strategy, platforms, tools, and processes; coordinates engineering, hardware, supply chain, operations, and security teams; manages roadmaps, governance, risks, metrics, and release alignment; and promotes generative AI capabilities to improve planning, engineering efficiency, reliability, and time to market. The role also coaches program managers and secures executive support for company-wide initiatives.

Drive technical sales and solution adoption through demonstrations, proofs of concept, hackathons, and architecture workshops. Partner with enterprise platform and engineering teams to design secure, scalable solutions using Microsoft Azure, Dynamics 365, Power Platform, and AI capabilities. Resolve technical blockers, influence solution architecture, support production deployments, build customer relationships, and represent Microsoft through technical thought leadership.

Lead end-to-end data science projects: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, operationalize models at scale, run experiments, drive ethics/privacy, partner with customers and teams, and coach cross-disciplinary colleagues.

Leads and develops a team of Azure Solution Engineers serving public-sector customers. Coaches technical discovery, architecture design, demonstrations, workshops, prototypes, proofs of concept, and customer technical engagements. Drives Azure and AI growth, sales execution, pipeline progression, forecasting, CRM hygiene, executive relationships, and partner collaboration. Ensures secure, scalable solutions and effective transitions to deployment, adoption, and customer success.

Provides technical leadership for AI framework and model-serving initiatives at cloud scale. Owns architecture, roadmaps, performance optimization, benchmarking, observability, and multi-release execution across models, compilers, runtimes, services, GPUs, and silicon. Leads cross-team alignment, makes architectural decisions, mentors engineers, performs hands-on implementation and debugging, and drives measurable improvements in model onboarding, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.