Top AI Specialist Jobs in Denver & Boulder, CO

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.

Design, develop, and deploy Agentforce AI agents and custom actions on the Salesforce platform. Build Apex classes, LWCs, flows, and API integrations with Data Cloud and legacy federal systems. Enforce AI safety, federal security/compliance, support testing/UAT, and enable secure DevSecOps/CI/CD deployments in cleared environments.

Design, develop, and deploy Agentforce AI agents and custom actions on Salesforce. Build Apex, LWCs, flows, and secure API integrations with legacy federal systems and Data Cloud. Ensure AI safety, compliance, testing, and support CI/CD/DevSecOps practices in cleared federal environments.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Create, optimize, schedule, and publish blog and social content about AI applications. Test headlines, landing pages, and ads; review analytics, predict opens/clicks/conversions, write performance reports, and personalize curated content.

Verify and reconcile hearing data across sources, build and maintain lightweight automation and AI-assisted verification workflows, troubleshoot data pipelines, respond to tickets, and send verified schedules to attorneys while meeting daily quality targets.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.

Join an internal AI enablement team to assess workflows, build prompt-based automations and lightweight apps, coach business teams, test and document tools, track user skill development, research AI platforms, and ensure governance and security compliance.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

Develop and optimize prompts, context management, and multimodal prompting workflows for LLM-powered products. Collaborate with Customer Success to iterate on prompts, review conversations and feedback, document and teach prompting best practices, and build small prototypes using Python and low-code tools to test complex prompting and data workflows.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead discovery and build AI-enabled operational workflows across R&D and business functions. Translate requirements into practical solutions, own design-to-launch, optimize adoption, and manage Marketing Operations (campaigns, automation, tech stack). Measure outcomes, document solutions, and ensure alignment with shared AI standards.

The SAP AI Specialist will integrate AI within SAP systems, optimizing capabilities using SAP Joule and BTP AI services, and developing predictive analytics and automation solutions.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Lead change management for AI-powered tools and workflows: assess impacts, build adoption plans, create training and communications, coach leaders and enablement teams, recruit change champions, track adoption metrics, and share learnings across the Change Management team.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.

Evaluate and improve LLM financial reasoning by designing real-world finance tasks, creating reference solutions, scoring AI outputs with structured rubrics, refining evaluation frameworks, and collaborating with researchers to raise data quality and model performance. Must provide detailed feedback and identify gaps to enhance AI across finance use cases.