Top AI Jobs in Denver & Boulder, CO

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

Leads and grows a perception AI engineering team building autonomous spacecraft capabilities, including synthetic data generation, multi-target tracking, sensor fusion, camera calibration, object detection, and edge deployment. Provides technical direction, defines validation standards, owns the team roadmap, coordinates cross-functional delivery, manages hiring and development, and ensures reliable performance under spacecraft compute, power, and operational constraints.

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

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.

Lead Engine’s internal AI Platform organization and technical strategy. Own the LLM gateway, agent frameworks, evaluation systems, developer-experience tooling, automation APIs, RAG and agent data infrastructure, observability, security, and cost controls. Build the initial platform hands-on, establish a unified enterprise AI stack, partner with Applied AI and Workforce Transformation leaders, and scale the organization through senior engineering leadership. Drive the Velocity program toward increased delivery autonomy and adoption across engineering.

Design, develop, deploy, and support AI solutions including generative AI applications, agents, workflow automation, document intelligence, and retrieval-augmented generation. Partner with business and IT teams to identify use cases, integrate enterprise platforms and data sources, establish prompt and evaluation standards, support AI governance and security, monitor solution performance, and train employees on responsible AI adoption.

Lead AI agent build and DevOps workstreams within a data and analytics practice. Manage client accounts and teams, design cloud-based analytics and BI solutions, validate data integrity, develop scalable visualizations (QlikView/Spotfire), and mentor staff to improve data pipelines and client outcomes.

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.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

Design, build, and maintain scalable full-stack applications; collaborate with cross-functional teams; integrate AI and agentic systems to enhance product features; ensure performance, fix bugs, and resolve bottlenecks.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Lead go‑to‑market and close enterprise deals for AI/GenAI healthcare solutions across payers, providers, PBMs, and life sciences. Own revenue targets, shape solutions with architects and product teams, run POCs and demos, craft proposals and pricing, and present ROI/value to CXO stakeholders.

Lead client engagements in insurance data, analytics, and AI: define roadmaps, run discovery sessions, design solutions, manage delivery and teams, develop proposals, and ensure DataOps, cloud (AWS), governance, and best practices across AI and analytics initiatives.

Build and operate AI-driven customer acquisition infrastructure, including outbound workflows, enrichment pipelines, lead routing, personalization, audience scoring, campaign automation, experimentation, and attribution dashboards. Partner with demand generation, lifecycle marketing, data analytics, product marketing, marketing operations, and sales to translate growth objectives into scalable automated systems.

Define clinical reasoning, safety boundaries, evaluation scenarios, datasets, rubrics, and acceptance thresholds for AI-enabled chronic disease products. Analyze failures and edge cases, support clinical validation and outcomes research, interpret clinical and EHR data, and collaborate with Product, Engineering, AI/ML, Data, informatics teams, and clinical stakeholders on integrations and workflows.

Design, build, and maintain optimization technology, full-stack systems, and data-intensive scheduling infrastructure. Improve optimization algorithms using linear optimization, machine learning, and generative AI. Lead complex technical initiatives, establish testing and observability, support scalable operations, troubleshoot customer issues, participate in on-call rotations, and mentor engineers while partnering closely with product and engineering teams.

Architects and develops AI-powered systems, tools, agents, backend services, APIs, and experimentation frameworks using foundational AI models. Integrates AI capabilities with microservices, AWS, Snowflake, and complex data systems while ensuring scalability, reliability, and maintainability. Translates business problems into technical solutions, prototypes AI applications, collaborates with product and engineering teams, evaluates emerging AI technologies, and documents system designs and integration patterns.

Develop, train, and evaluate machine learning models for space-domain applications including object classification and anomaly detection. Build data ingestion, preprocessing, feature engineering, and model evaluation pipelines; conduct experiments; track results; and write clean, testable Python code. Collaborate with senior engineers while contributing to AI capabilities supporting space security and autonomous systems.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead and grow a data science and analytics team supporting Growth product initiatives. Partner cross-functionally to shape strategy, design measurement frameworks, run experiments (A/B tests), and build AI/ML-powered product features. Balance hands-on analysis, rigorous evaluation, and executive-facing communication to drive product impact and scale.

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, evaluation and observability capabilities, and workflows that turn insights into action. Work hands-on with large and small models, durable orchestration, cloud deployment, inference-cost optimization, and high-volume observability data. Establish reusable engineering patterns, collaborate with product and platform teams, and mentor through strong technical contributions.

Design, build, and operate agentic AI systems end-to-end for Professional Services. Translate stakeholder needs into secure, scalable multi-agent architectures, define performance benchmarks, manage deployments and incident response, advise leadership, mentor teammates, and maintain runbooks and production tooling including on-call responsibilities.