Top AI Jobs in Denver & Boulder, CO

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.

The Advisory Agentic Technologist will be the Subject Matter Expert in identity management, driving technical success and strategy, collaborating on agentic AI innovations, and influencing product development, with a focus on the US, Canada, and Latin America.

Design, build, and ship production-grade agentic AI workflows using LangGraph, Temporal, and Pydantic. Implement AI observability with LangFuse, set AI engineering standards (RAG, prompt management, tool-calling), benchmark LLMs, deploy cloud AI (containerization, cost management), and mentor engineers while supporting enterprise SLA, security, and compliance needs.

As a GTM AI Engineer, design and execute AI-driven workflows for Superhuman's go-to-market stack, improving automation in sales processes and team collaboration.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

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.

As an AI Engineer, you will build and scale AI business applications, focusing on generative AI. Responsibilities include rapid prototyping, applying software engineering best practices, and providing production support.

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.

Use advanced analytics, statistical techniques, and machine learning to extract insights from large datasets. Design data solutions and pipelines, build predictive models (R, MATLAB), and apply TensorFlow and Scikit-Learn for deep learning and NLP. Collaborate with teams and clients, deliver quality work, and adhere to firm standards.

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

Design, prototype, and deploy LLM-powered agents, RAG workflows, and automations that accelerate internal teams and customer-facing product features. Integrate AI systems with SaaS tools, build reusable components and evaluation frameworks, embed with business teams to deliver measurable outcomes, and establish standards for responsible AI, monitoring, and cost control across the company.

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

Design, build, and own production AI agents and automations for marketing. Integrate and instrument the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), implement predictive scoring and personalization, monitor systems for reliability, and collaborate with marketing, RevOps, and sales to translate problems into deployable software.

Bridge AI models and field operations to deploy practical AI solutions: prepare data governance, integrate enterprise chatbots, enable wearable AI and AR onboarding, build agentic "AI manager" workflows, and optimize prompts, procedures, and automation to improve technician productivity and service quality.

Own enterprise AI strategy and launch the PureSpectrum AI Academy. Curate an approved AI tool stack, create function-level AI playbooks, manage an active AI project portfolio, partner with engineering to implement API-connected workflows, and drive measurable adoption, automation, efficiency, and ROI across functions while reporting program status to leadership.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

Lead AI agent build and DevOps workstreams within a Data & Analytics practice. Develop and implement BI and cloud analytics solutions, build visualizations (QlikView, Spotfire), validate data integrity, manage client relationships, identify optimization opportunities, and mentor teams to ensure project delivery and performance.

Lead managed-services teams to design and deliver AI agent builds and DevOps-enabled analytics solutions. Develop data architecture, advanced analytics and visualizations, ensure data integrity/security, manage client accounts, mentor staff, and drive continuous improvement to generate strategic insights and business value.