Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Provides technology consulting and technical delivery for U.S. government customers, focusing on expanding cloud and Microsoft technology adoption. Implements assigned technical solutions, participates in customer and stakeholder meetings, identifies risks, supports operational readiness, learns new technologies, and contributes to intellectual property and best-practice development. The role requires an active Top Secret/SCI clearance and U.S. citizenship.

Leads strategic operations for Microsoft’s Core commercial organization, managing executive business rhythms, governance, operating cadence, and cross-organizational alignment. Partners with senior and regional leaders to translate strategy into measurable execution, surface risks and dependencies, improve decision-making, and ensure accountability. Establishes scalable processes, tools, and standards while driving continuous improvement and adoption of AI-enabled capabilities.

Leads strategic sourcing, contract negotiations, commercial management, supplier performance, and risk mitigation for general contractors and critical service providers supporting large-scale data center construction. Partners with Legal, Construction, Cost Management, Engineering, Procurement, and Operations teams to manage contracts, changes, claims, compliance, forecasting, and continuous improvement. Oversees executive stakeholder relationships and ensures suppliers deliver against project, budget, schedule, and performance requirements.

Design, build, and operate distributed storage and file-system platforms for cloud-scale AI training and inference. Architect storage and caching for Kubernetes and GPU workloads, improve performance, reliability, observability, and resiliency, diagnose cross-layer production issues, and lead architecture reviews. Partner across infrastructure, networking, operating systems, and AI platform teams while mentoring engineers and shaping long-term storage strategy.

Lead the architecture, technical strategy, and roadmap for Microsoft's Windows ML compiler stack. Design high-performance compiler infrastructure, execution engines, optimization frameworks, and developer tools supporting CPU, GPU, and NPU workloads. Drive NPU enablement, graph optimization, scheduling, memory management, code generation, and hardware abstraction. Partner with silicon vendors and internal teams, influence AI hardware and platform strategy, lead cross-team initiatives, and mentor engineers developing on-device and generative AI capabilities.

Designs and develops foundational Azure compute platform technologies. Leads architecture and design for complex systems, writes secure and performant production code, establishes test strategies, performs code reviews, debugs system issues, and drives cross-team technical alignment. The role also applies AI-enabled engineering practices, improves engineering quality, and supports security hardening across cloud infrastructure solutions.

Conducts econometric, causal, statistical, and optimization analyses to improve operational efficiency, resource allocation, product performance, and business outcomes. The role defines efficiency measures, develops forecasting and optimization tools, partners with product and engineering teams on data instrumentation and implementation, and communicates findings to executives through clear reports.

Lead technical pre-sales engagements for Microsoft cloud database and analytics products. Deliver PoCs, demos, hackathons, and architecture workshops; design secure, scalable solutions; resolve technical blockers; collaborate with engineering; and evangelize Fabric, Databricks, Purview and Azure database technologies to accelerate customer migrations and adoption.

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.