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

Build production AI/ML software for supercomputers and AI infrastructure, including anomaly detection, forecasting, root cause analysis, automation, and operational intelligence. Develop services with Go, Python, and React; integrate machine learning models, LLM workflows, agentic systems, and analytics. Own the lifecycle from data engineering and model development through deployment, monitoring, and improvement while collaborating with engineering, architecture, product, and customers.

Leads customer discovery, virtualization solution design, migration planning, product requirements, proofs of concept, pilots, and early-access programs. Partners with enterprise customers, sales, presales, and engineering teams to develop HVM/KVM-based solutions, support strategic deals, communicate competitive positioning, and influence the product roadmap. Requires deep virtualization, networking, Linux, storage, and infrastructure expertise, plus strong executive and technical communication skills.

Leads pre-silicon ASIC design verification across methodology, test planning, SystemVerilog/UVM testbench development, scoreboards, checkers, functional coverage, regression triage, and sign-off. Develops automation and applies AI-assisted tools to improve verification. Provides technical mentorship, supports leadership development, and drives VLSI innovation. The role focuses on high-quality verification of block and integration-level designs in a distributed team environment.

Develops and maintains BIOS and platform firmware for server and high-performance computing systems. Responsibilities include platform bring-up, firmware implementation, hardware initialization, debugging, testing, integration, and release readiness. Collaborates with hardware teams, BIOS vendors, silicon partners, and software engineers while coordinating projects and mentoring less-experienced staff. The role requires expertise in C/C++, UEFI, Linux development environments, firmware testing, and complex hardware-software integration.

Leads go-to-market strategy and operational roadmaps for HPE Private Cloud AI products. Defines value propositions, customer segments, business cases, and market requirements while partnering with sales, marketing, and product teams. Serves as the voice of customers and field sellers, influences cross-functional stakeholders, mentors product managers, and drives positioning, roadmap development, and customer engagement across industry verticals.

Designs, develops, and executes manual and automated tests for embedded software. Responsibilities include creating test plans, debugging issues, analyzing system designs, maintaining test coverage, collaborating with software engineering partners, resolving technical problems, and improving testing methodologies, tools, and processes. The role requires embedded software testing experience, programming skills in Python, C, or Go, and familiarity with embedded Linux, device drivers, computer architecture, and communication protocols.

Owns complex, cross-functional engineering and product lifecycle programs from concept and NPI through release, sustaining, and end-of-life. Responsibilities include integrated schedule and budget management, dependency and risk resolution, governance, milestone recovery, executive communications, process improvement, and coordination across Product, Engineering, Manufacturing, suppliers, and partners. The role also mentors team members and drives delivery outcomes in Agile environments.

Leads complex, cross-functional engineering and product lifecycle programs from concept and NPI through release, sustaining, and end-of-life. Owns integrated schedules, budgets, resources, governance, risks, dependencies, recovery plans, stakeholder communications, and milestone readiness. Partners with Product, Engineering, Manufacturing, suppliers, and customers to deliver products on time and within budget. Mentors staff and drives process improvements, execution predictability, and delivery performance.

Leads complex AI and cloud-native incubation projects, designing and implementing scalable services across public cloud, datacenter, and edge environments. Develops Generative AI, microservices, and distributed-system solutions; evaluates emerging technologies through prototypes and research spikes; guides architecture, security, reliability, testing, CI/CD, and observability. Leads small multidisciplinary engineering teams, collaborates with stakeholders, mentors engineers, and advances innovative capabilities across multiple parallel projects.

Leads large-scale, multi-site private cloud and infrastructure programs from presales through deployment, migration, cutover, hypercare, and managed services transition. Coordinates engineering, supply chain, services, PMOs, partners, and customers; owns integrated schedules, governance, RAID logs, risk and change management, executive communications, and recovery plans for troubled programs. Requires strong technical knowledge of compute, storage, networking, virtualization, and global migration initiatives.