Top AI Automation Jobs in Denver & Boulder, CO

Leads the technical design, architecture, development, deployment, and lifecycle management of AI-powered agents and automation solutions. Mentors AI engineers, establishes engineering standards, conducts code reviews, makes architectural decisions, resolves complex technical issues, and ensures scalable, secure, maintainable solutions. Partners with business and IT leaders to translate strategy into technical roadmaps while evaluating emerging technologies and improving team capabilities.

Leads customer discovery and end-to-end deployment of Workday AI agents in enterprise environments. Configures, debugs, and improves solutions using customer data and workflows; manages Early Access customers and executive stakeholders; triages issues; translates feedback into product improvements; defines graduation criteria; and creates deployment playbooks and documentation. Requires deep Workday knowledge, enterprise implementation experience, entrepreneurial ownership, and travel to customer sites up to 20%.

Leads advanced analytics, AI, automation, and scientific computing initiatives supporting pharmaceutical clinical development. Translates scientific and business requirements into scalable analytical products, software specifications, decision-support tools, and production automation. Partners across biometrics, clinical development, IT, and business teams; evaluates emerging AI technologies; improves regulated workflows; establishes value metrics; drives adoption and change management; and mentors technical talent.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Build and deploy AI-enabled solutions for Marketplace operations and commercial challenges. Identify opportunities, frame ambiguous business problems, develop prototypes using enterprise data and AI/LLM tools, validate business value, and transition successful solutions into production. Partner with business, product, technology, and data teams; drive adoption, measure outcomes, coordinate initiatives, mentor team members, and enhance reusable platforms and frameworks.

Own the enterprise AI strategy, roadmap, governance, investment priorities, and measurement framework. Identify and prototype high-value AI use cases, guide pilots into production, establish responsible-AI standards for sensitive data, and communicate outcomes to executives. Build adoption through enablement and reusable practices while coordinating technology, business, legal, security, data, and vendor partners. Lead the emerging AI strategy function and hold teams accountable for delivery and value realization.

Supports enterprise growth through strategic market research, business analytics, account intelligence, and AI innovation. The intern will research companies and competitors, analyze market trends, prepare strategic presentations, and help design and test AI agents and intelligent workflows for automated research and reporting. The role collaborates with Sales and Marketing while identifying ways to improve productivity and decision-making using generative AI and emerging technologies.

Build and maintain AI-powered workflows, agents, automations, internal tools, and production systems for creative ideation, copy generation, video pipelines, reporting, and client delivery. Integrate LLMs and third-party APIs, ship rapidly, iterate based on real usage, and develop practical tools that improve marketing operations.

Leads enterprise AI strategy, product roadmapping, and cross-functional transformation initiatives. Identifies and scales high-impact AI use cases, oversees solution development and deployment, redesigns workflows, drives adoption, advises executive leadership on AI investments and governance, and establishes KPIs for efficiency, cost, quality, and client outcomes. The role also mentors associates and manages stakeholders across business, operations, and technology teams.

Develop and maintain production AI-powered software for mission-critical USPS systems. Design distributed, microservice-based architectures, improve reliability and scalability, identify bottlenecks, and modernize existing systems. Work across the technology stack, communicate architectural decisions, mentor junior developers, and use AI and automation tools to improve engineering outcomes. The role is remote and requires the ability to obtain Public Trust clearance.

Own enterprise customer deployments of agentic AI and hybrid automation solutions from discovery through production. Build AI agents using Claude, Gemini, and GPT; integrate RPA, document AI, Python services, and enterprise systems; deploy workloads on Google Cloud; and implement evaluations, guardrails, monitoring, and CI/CD. Mentor automation developers, lead customer workshops, measure ROI, and provide field insights to Product and Engineering.

Lead the architecture and development of agentic engineering capabilities across the software development lifecycle. Build AI-powered workflows, agents, integrations, guardrails, evaluation systems, and observability patterns. Establish engineering data architecture and systems of record while advising teams on adopting agentic development practices. Drive scalable implementation, organizational adoption, measurement, and continuous improvement of AI-enabled engineering operations.

Build, test, and support AI-powered applications and workflow automations using Microsoft Power Platform, GPTs, agents, APIs, and automation tools. Configure prompts, integrations, and knowledge sources; troubleshoot workflows; conduct testing and UAT; document solutions; support deployments and users; and follow information security practices. The role offers guided development for an early-career engineer with foundational programming, AI, automation, and software skills.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Build and deploy AI-powered automation workflows for marketing, growth, content, sales collateral, social distribution, and community operations. Responsibilities include auditing existing processes, automating blog production and publishing, encoding brand voice, integrating platform APIs, implementing human approval steps, documenting workflows, and handing them off to the team.

Own Cerby’s AI agents for API catalog generation, browser workflow creation, and self-healing automation. Take existing systems into production using durable workflows, observability, evaluation benchmarks, cost controls, and security protections. Responsibilities include detecting and repairing automation drift, managing credential isolation and prompt-injection risks, defining threat models, partnering with engineering teams, writing design documentation, mentoring contributors, and providing on-call ownership after launch.

Leads consulting engagements that design, build, evaluate, and deploy enterprise agentic AI and infrastructure automation solutions. Responsibilities include multi-agent orchestration, LLM and model-platform integration, RAG, tool and API connectivity, guardrails, observability, testing, and production rollout. The role advises client executives, translates business needs into AI strategies, mentors engineers, develops reusable architectures and evaluation assets, and drives responsible, measurable AI outcomes.

Design, build, and maintain AI-enabled workflow orchestration and automation systems for legal service delivery. Implement integrations between AI platforms, CRMs, document systems, client portals, and payment systems. Develop event-driven pipelines, retrieval and prompt orchestration, agent workflows, and observability. Monitor reliability, troubleshoot integrations, support compliance and governance, and document architectures and operational standards.

Build and deliver enterprise AI agent solutions using Microsoft Copilot Studio, Microsoft Foundry, Microsoft 365 Copilot, Azure, and Power Platform. Design agent architectures, integrations, grounding, evaluations, automations, and responsible AI controls. Implement governance, security, compliance, lifecycle management, ALM, DLP, identity, monitoring, and cost optimization. Advise customers, translate business requirements into production solutions, create reusable technical assets, and facilitate technical discussions across customer and internal teams.

Leads company-wide data science priorities, KPI frameworks, measurement standards, causal modeling, scenario planning, and agentic analytical automation. Builds reproducible SQL and Python workflows, validates predictive and causal relationships, establishes trusted metrics, partners with Finance, Product, Commercial, Engineering, and Data Engineering, and mentors scientists. The role drives adoption of governed self-service analytics and communicates assumptions, uncertainty, and business trade-offs to leadership.

Develop and scale AI, Microsoft Copilot, Power Platform, and intelligent automation solutions across Buildings. Responsibilities include designing AI agents and workflows, identifying automation opportunities, delivering training and adoption programs, supporting governance, integrating Microsoft platforms, and measuring business value through analytics and reporting.

Build and deploy AI agent systems that automate complex business processes. Analyze workflows, design and configure agents, integrate AI with enterprise applications, develop connectors and APIs, and establish evaluation and monitoring systems. The role requires expertise in cloud AI services, LLMs, NLP, Python, integration platforms, conversational AI, RAG, vector databases, APIs, and SQL/NoSQL systems. The engineer will also explore emerging AI technologies and mentor junior developers and system administrators.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Identifies business opportunities for AI and automation, gathers and documents requirements, develops business cases, supports solution design and delivery, facilitates stakeholder collaboration, assists with testing and change management, and tracks project outcomes, reporting, and benefits realization.