Top AI Jobs in Denver & Boulder, CO

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Lead a team of 4–8 AI engineers while remaining hands-on with architecture, code reviews, debugging, and technical decisions. Own delivery of production AI systems, including LLM applications, agentic workflows, document extraction, ETL pipelines, observability, evaluation, and monitoring. Partner with product, platform, data engineering, recruiting, and customers to build reliable, scalable AI features and grow engineering talent.

Designs and deploys AI-powered features and scalable AI/ML services across SaaS products. Responsibilities include translating business problems into AI solutions, integrating large language models, preparing data, evaluating model performance, writing Python, building secure deployment infrastructure, and collaborating with product, data, and cloud operations teams. The role requires production AI/ML experience, scalable data infrastructure expertise, AWS familiarity, and modern DevOps practices.

Leads CDW’s AI advisory consulting portfolio, including strategy, governance, operating models, adoption, prioritization, and roadmaps. Develops consulting methodologies, delivery frameworks, sales enablement, and thought leadership. Advises executives and customers, leads complex presales pursuits, shapes proposals and business cases, oversees delivery quality and risk, evaluates technical feasibility, and mentors consulting and presales teams.

Own and architect core AI pharmacy products, including prior authorization pipelines, Epic integrations, patient communications, and production agentic systems. Build hands-on software using LLMs, RAG, function calling, and evaluation workflows in a regulated healthcare environment. Set engineering standards, make architectural decisions, manage delivery across product milestones, and collaborate across teams to ship reliable solutions that improve pharmacy operations.

Lead AI product strategy and roadmap for Spectrum News. Translate editorial and business needs into product requirements, collaborate across teams, guide development of personalization, recommendations, discovery, and newsroom productivity AI features, ensure responsible AI governance, measure impact with analytics, and communicate vision to stakeholders.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Build and deploy AI-powered tools for Rula’s business and clinical teams by observing workflows, rapidly delivering production software, measuring usage and impact, and enabling teams to operate tools independently. The role requires privacy-by-design practices, rigorous AI evaluation, customer-centric discovery, and integration with complex legacy systems. Staff engineers may optimize LLM costs and quality while creating reusable building blocks for future teams.

Leads enterprise AI solution architecture across healthcare, defining scalable patterns for generative AI, agentic AI, machine learning, intelligent automation, and cloud platforms. Establishes governance, responsible AI controls, reference architectures, and technology standards while guiding engineering teams through production deployments. Partners with executives, product leaders, data scientists, security, legal, and compliance teams; evaluates emerging technologies; prototypes AI solutions; and mentors architects and engineers. Requires deep experience with LLMs, RAG, AI agents, vector databases, healthcare systems, distributed architectures, and enterprise technology governance.

The Staff AI Engineer will analyze AI quality, implement improvements, manage projects, collaborate with teams, and shape AI capabilities in a remote-first environment.

Structures and optimizes knowledge base content for generative AI retrieval and agent desktop systems. Analyzes more than 100,000 weekly GPT prompts to diagnose inaccurate responses, performs root-cause analysis, and implements content fixes. Translates frontline feedback into structured updates, develops AI content standards, creates HTML/CSS support materials, and collaborates with subject matter experts, business partners, and developers to improve knowledge accuracy and operational efficiency.

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.

SynX Therapeutics, a biotech start-up, invites speculative applications for future roles related to drug discovery and engineered biology.

Manage the Dev AI engineering team building AI infrastructure, developer tooling, agentic coding tools, workflow platforms, SDKs, and AI-assisted migration systems. Shape technical strategy, partner with senior engineering leaders, evaluate emerging AI technologies, consult with internal teams, build stakeholder relationships, and coach distributed engineers. The role emphasizes developer productivity, cross-functional collaboration, rapid experimentation, and measurable impact across Airbnb.

Leads enterprise AI research and development strategy, combining classical and generative AI into production-grade platforms, agentic systems, and customer products. Builds and scales teams of applied scientists and engineers, advances hybrid AI architectures, establishes experimentation and evaluation practices, and embeds responsible AI principles. Partners with senior leaders, academia, and industry to commercialize research and deliver measurable business impact.

Design, build, deploy, and operate production AI agents and multi-agent systems for insurance workflows. Responsibilities include agent orchestration, APIs, RAG pipelines, evaluation frameworks, regression testing, observability, production troubleshooting, and reliability improvements. The role requires hands-on Python software engineering, LLM application development, cloud infrastructure, and collaboration in end-to-end product pods.

Lead the technical direction, architecture, and development of Compass, an LLM-powered agent platform. Design multi-agent systems, MCP and A2A integrations, orchestration, evaluation, and observability infrastructure. Drive cross-team technical projects, production support, engineering quality, mentoring, and adoption of AI-assisted development practices. Partner with Product, QA, Design, Operations, and Engineering stakeholders to deliver reliable agentic systems.

Architect and deploy production-grade autonomous AI agents for semiconductor manufacturing. Responsibilities include designing multi-agent systems, RAG and agent pipelines, evaluation and profiling frameworks, MCP/A2A integrations, security controls, and Kubernetes-based CI/CD deployments. The role requires optimizing inference workloads, transforming AI prototypes into scalable systems, collaborating with data teams and manufacturing experts, and mentoring engineers.

Lead the AI Platform team in building reliable, secure, observable infrastructure, shared services, deployment patterns, and operational practices for AI capabilities. Set technical priorities, coordinate cross-team dependencies, guide architecture and production operations, improve developer experience, and coach engineers while contributing to complex technical work.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Principal AI Architect responsible for defining and governing enterprise Generative AI and AI/ML architectures. Designs LLM, RAG, vector database, MCP, multi-agent, and orchestration solutions; establishes reusable patterns, security, governance, and responsible AI standards; leads architecture workshops; partners with product, business, data, platform, and application teams; and provides technical direction for scalable, secure, production-ready AI capabilities.

Leads expeditionary AI discovery, assessment, prototyping, and delivery for government customers. Builds generative AI systems using LLMs, RAG, agentic workflows, and applied machine learning; integrates models with APIs, data services, cloud infrastructure, and testing. Engages stakeholders, translates requirements into technical plans, briefs technical and senior audiences, estimates staffing and effort, and guides prototypes toward operational deployment. The role also shapes AI roadmaps, transformation frameworks, team formation, and customer strategies.

Deploys and operationalizes AI solutions across the enterprise, translating business needs into technical requirements and ensuring data, infrastructure, security, governance, scalability, and adoption readiness. The role configures integrations, data pipelines, workflows, and AI services; converts prototypes into production solutions; troubleshoots deployments; enables stakeholder adoption; and creates repeatable implementation practices. It partners with business, product, data science, AI engineering, and platform teams, particularly within regulated environments.