Top Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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.

Lead development of production-grade AI solutions, advise on large projects, and manage high-performing teams. Drive advanced analytics, GenAI chat experiences, stakeholder alignment, and continuous improvement to deliver impactful, standards-compliant results.

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.

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.

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.

Lead design and implementation of agentic AI workflows and integrations for Acquia DAM. Build, ship, and observe production AI features (auto-tagging, search, governance), set AI engineering standards, evaluate models and tooling, mentor engineers, and represent AI architecture to product and customers.

Take Deepgram's speech models and optimize, compile, and run them on resource-constrained embedded and edge hardware. Work across model compression, runtime performance (C/C++/Rust), RTOS/bare-metal and embedded Linux environments, vendor NPUs/DSPs and inference runtimes, benchmarking, deployment pipelines, OTA updates, and partner with silicon vendors to enable real-time, low-power on-device voice experiences.

Architect and scale an internal AI platform and APIs to integrate LLMs into developer workflows. Build autonomous agents, RAG systems, and production-grade tooling to boost developer productivity, ensure reliability, security, and cost-efficiency, and collaborate across product, infrastructure, and security teams.

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.

This role involves defining AI architecture, improving system quality, leading teams, and building production-ready AI systems at Drata.

As a Staff AI Engineer, you'll lead AI product development, overseeing technical direction, system deployment, and model evaluation while collaborating across teams.

The role involves designing AI systems for mental healthcare, focusing on building scalable, production-grade systems that enhance patient engagement and clinical operations. Responsibilities include setting technical standards and ensuring safety and reliability while working with advanced AI technologies.

Lead development and delivery of healthcare AI/GenAI solutions for health systems—architect RAG and agentic workflows, manage global MLOps and model governance, engage executive stakeholders, and drive production-grade use cases across clinical, financial, and operational domains.

Lead development and delivery of AI and GenAI solutions for health systems. Serve as strategic advisor, manage teams, ensure HIPAA-compliant deployments, implement MLOps and model governance, translate clinical workflows into AI use cases, and drive stakeholder alignment and operational excellence.

Senior individual contributor who defines enterprise AI architecture, builds reusable platform components and governance controls, drives observability and cost attribution, mentors engineers, and partners across Security, Legal, Data, and product teams to enable secure, measurable AI adoption.

Build and operate production AI capabilities—agents, prompts, connectors, automations, and telemetry—to improve productivity. Deliver reusable components, integrate AI with enterprise systems, enforce responsible AI controls, instrument costs and ROI, and collaborate across security, legal, data, and business teams to scale safe, measurable AI adoption.

Hands-on individual contributor building and operating enterprise AI capabilities: agents, prompts, connectors, automations, and telemetry. Partners with stakeholders to convert workflows into production-quality, secure, measurable AI solutions, create reusable components, enforce governance controls, optimize cost and ROI, and enable cross-functional adoption and observability.

The Senior Engineer will architect self-healing infrastructure, design AI orchestration workflows, automate incident resolution, and establish AI best practices, focusing on Generative AI and observability.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Contribute to building and hardening micro-apps and AI integrations on a shared GCP platform. Complete bug fixes and small features, participate in code and design reviews, apply security and software development best practices, monitor applications and follow runbooks, and use AI tools to assist development, testing, and documentation while learning from senior engineers.

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.

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.

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.

As a Staff Software Engineer, you'll design, build, and test Gusto's core platform services, mentor engineers, and collaborate with various teams to solve complex engineering problems.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.