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

Provides technical pre-sales and consulting support for Microsoft’s GitHub, Visual Studio, Azure AI, and cloud developer platforms. Leads demos, proofs of concept, hackathons, code-with sessions, and architecture workshops for enterprise development teams. Advises customers on secure, scalable cloud-native architectures, DevOps, CI/CD, and AI-assisted software development; resolves technical objections; collaborates with engineering; and promotes Microsoft solutions through customer and developer communities.

Lead product security initiatives for cloud, AI, and enterprise platforms. Responsibilities include threat modeling, security architecture reviews, identifying systemic weaknesses, developing secure-by-design guidance and reference architectures, advising engineering and product leaders, leveraging AI and automation for scalable security assessments, investigating emerging attack paths, mentoring teams, and improving security review methodologies and tooling.

Lead definition of system and silicon architecture for Windows devices, translating workloads and product goals into SoC/system requirements. Drive silicon roadmaps, co-design across hardware and software teams, build workload/system models, define KPIs/tradeoffs (compute, memory, power, thermal, security), and align partners and engineering teams from early definition through silicon and product execution.

Lead technical pre-sales for enterprise AI applications: run demos, PoCs, hackathons, and architecture workshops. Design secure, scalable cloud-native AI solutions, resolve technical blockers, and advise customers on AI Foundry, Azure AI, Responsible AI, and AI management/security to accelerate adoption and deployment.

Owns field awareness, activation, adoption, utilization, reporting, and continuous improvement for Azure investment and offer programs. Coordinates launches, enables sales stakeholders, resolves execution blockers, governs field content, tracks KPIs and business impact, and translates insights into recommended actions. Leads global office hours, business reviews, feedback loops, and cross-functional collaboration across sales, operations, partners, marketing, tooling, and program teams to accelerate customer adoption, pipeline, revenue, and renewals.

Leads enterprise Azure sales strategy, pre-sales engagements, forecasting, territory planning, and strategic account growth. Advises customers on cloud, data, analytics, AI, applications, and infrastructure transformations; develops business cases, technical strategies, proofs of concept, and deployment roadmaps. Coordinates Microsoft teams, partners, and solution engineers to close deals, drive Azure consumption, generate pipeline, and deliver customer value. Mentors colleagues, shares industry insights, supports partner strategies, and acts as a trusted technical advisor and customer advocate.

Drive technical sales for Azure cloud and AI infrastructure solutions. Lead architecture sessions, workshops, demos, proofs of concept, and migration or modernization initiatives. Design secure, scalable hybrid-cloud architectures for Windows, SQL, Linux, PostgreSQL, Oracle, and enterprise applications. Advise customers on networking, resiliency, compliance, containers, AKS, Azure Arc, SAP, VMware, and partner technologies while collaborating with engineering and business stakeholders.

Lead technical strategy with channel partners across ASEAN to build repeatable Microsoft Cloud and AI Workforce offerings (Copilot, Power Platform, Agents). Drive architecture design, workshops, POCs, offer development, partner enablement, and co-sell execution to convert technical capability into scalable revenue and customer outcomes.

Build and maintain large-scale infrastructure for multimodal generative AI, including data processing, model pretraining, post-training, inference, and serving frameworks. Collaborate with research scientists and product engineers to resolve infrastructure challenges, optimize distributed CPU/GPU workloads, influence software and hardware architecture, and accelerate AI product delivery. The role also involves multimodal data processing, distributed training and inference, model evaluation, reinforcement learning, quantization, and technical project leadership.

Design, implement, and ensure quality of systems stack, tools, and SDK integration for AI frameworks. Collaborate with hardware and ML teams, apply engineering principles, write low-level/high-performance code, define architecture, estimate scope, and drive coding standards.