Top AI Jobs in Denver & Boulder, CO

Design and deliver custom AI-driven legal workflows, implement and scale post-sales solutions, define KPIs and success metrics, inform product strategy, partner with Customer Success to demonstrate ROI, and maintain objective, ethics-compliant processes and playbooks for plaintiff law firms.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

The Interaction Intelligence Program Manager leads the deployment of AI capabilities in the contact center, overseeing initiatives, technical oversight, and change management with a focus on ethical AI and stakeholder collaboration.

Lead discovery and delivery of AI-first AEC product capabilities. Define roadmap, prototype agentic LLM workflows, translate research into requirements, measure outcomes, and partner with UX, Engineering, and GTM to drive adoption and growth.

The Staff Applied AI Engineer will develop decision intelligence systems using machine learning and optimization, focusing on improving planning decisions and operational efficiency. Responsibilities include building models for revenue attribution, designing decision-support systems, and ensuring security in AI-driven capabilities.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

Design, build, and operate Jellyfish's Databricks Lakehouse and data/AI platform. Build ingestion, transformation, and delivery pipelines; govern data with Unity Catalog; enable BI, agentic analytics, metadata, lineage, and observability. Provide technical leadership, set architecture and standards, mentor peers, and collaborate with cross-functional stakeholders to make Databricks the foundation for analytics and AI.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Lead product management in AI-driven safety solutions, focusing on video-based safety products, managing a roadmap and collaborating across teams for customer impact.

The Senior GTM Engineer in AI Innovation will strategize and implement AI initiatives across Marketing, Sales, and Customer Success while also leading cross-functional efforts and managing a growing team.

The Principal AI/ML Engineer will develop AI/ML solutions for hardware and firmware validation, enhance test efficiency, and collaborate across teams to implement data-driven analytics and automation.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Embed with teams to audit workflows, build and productionize LLM/agent automations (using Claude and integrations), create reusable assets and guardrails, coach teams to self-sufficiency, and measure outcomes to prioritize future engagements.

Lead design and implementation of conversational and agentic AI solutions for clients, building voice and natural language interfaces, prototypes, and responsive web front-ends. Conduct user research and usability testing, collaborate with cross-functional teams to integrate AI platforms (Dialogflow, Amazon Lex, Azure OpenAI, AWS Bedrock), and apply human-centered design to optimize contact center workflows and customer experiences.

Lead development and implementation of conversational and agentic AI solutions for contact centers. Manage cross-functional teams, translate client requirements into technical specs, design responsive UIs using AngularJS/React/Vue, run usability testing, apply human-centered design, and mentor junior staff while building client relationships to ensure successful delivery of AI-driven products.

The role involves developing, testing, and validating Generative AI agents and maintaining automated testing standards. Responsibilities include mentoring junior associates, analyzing complex issues, and applying governance controls in AI-driven solutions.

Lead development and implementation of AI-powered contact center and conversational solutions. Guide cross-functional teams to design natural language interfaces using Dialogflow and Amazon Lex, prototype UIs with Figma, conduct usability testing and user research, validate data integrity and security, build stakeholder relationships, and coach teams to deliver high-quality, client-aligned AI products.

As an AI Engineering Manager at PwC, you will lead the design and operation of AI-powered platforms, mentor engineers, and ensure project delivery excellence while focusing on security and scalability.

Integrate and fine-tune existing AI models into product features, build evaluation frameworks and observability for production AI, collaborate with data science and engineering, and develop AI-powered application features using Python to improve user experience.

Lead the product strategy and roadmap for a centralized AI context management and model-management platform. Design integration patterns, paved roads, evaluation/observability frameworks, and enablement for internal teams. Partner with engineering and data teams to ensure context retrieval, model selection, and production-ready agentic experiences while driving adoption and measuring platform outcomes.

Design and implement AI capabilities, transition prototypes to production, build agent workflows, optimize data retrieval, and automate evaluation processes.

Lead GTM systems and applied AI for Revenue Operations: own non-Salesforce tech stack, drive GTM AI roadmap and COE, prototype and deploy AI workflows, govern data quality, optimize tooling, and manage a team of engineers and analysts.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Develop and implement AI solutions, optimize models, preprocess data, integrate AI into workflows, and collaborate with cross-functional teams.