Top Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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.

Build the execution layer for AI focusing on relational intelligence in natural conversation. Tasks include affect analysis, memory systems integration, prompt engineering, and cloud infrastructure setup.

As an AI Engineer III, you will design and improve AI-driven product features to enhance patient billing clarity and workflows in healthcare.

As an AI Engineer, you'll integrate AI solutions, optimize models, collaborate on technical solutions, and shape the technical direction at Hiya.

AI Engineers at Hiya develop and integrate AI solutions, conduct model evaluations, and optimize large language models, collaborating with cross-functional teams.

AI Engineers at Hex will build AI experiences, manage search and context architecture, and work on scalable AI applications. Responsibilities include running experiments, developing infrastructure, and leading initiatives for new capabilities.

Lead end-to-end post-training lifecycle for LLMs: curate SFT and preference datasets, run SFT and preference optimization, evaluate and monitor models, deploy agentic LLM systems, integrate into low-latency production, and provide technical leadership for alignment, safety, and versioning.

The role involves designing, implementing, and optimizing AI models for railroad operations while ensuring integration and collaboration across teams.

The role involves building and scaling the Enterprise AI Platform at Wasabi, designing AI-powered solutions, implementing scalable services, and ensuring robust data governance.

Zapier seeks an Applied AI Engineer to develop AI-driven automation tools. Responsibilities include working with large language models and improving AI performance, scalability, and reliability.

Lead innovations in data pipeline infrastructure, develop high-volume data services, and collaborate with engineers on architectural designs and documentation.

The role involves shipping full-stack AI projects, designing experiments for AI features, and optimizing AI infrastructure while collaborating with teams.

Design and develop scalable AI/ML solutions while mentoring teams and collaborating with cross-functional partners to enhance customer experience through data-driven insights.

Lead design and scaling of automated test frameworks across UI, API, integration, and performance layers. Integrate AI-enabled test generation and monitoring, embed tests in CI/CD pipelines, ensure audit-ready documentation for GxP/21 CFR Part 11 compliance, and collaborate with Engineering, DevOps, and Quality to increase automation coverage and release confidence.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Lead the design and implementation of AI-based products, collaborate with stakeholders for strategic guidance, and build scalable systems while mentoring teams. Required to have significant experience in coding and AI technologies.

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

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Lead design and operation of AI/ML platform, mentor engineers, ensure operational excellence, and collaborate on scalable technical roadmaps.

The Senior QA Engineer will develop scalable AI-assisted test automation frameworks for various platforms, focusing on quality engineering, collaboration with development teams, and continuous improvement of testing strategies.

Lead architecture and implementation of high-throughput, distributed backend systems for agentic AI and MCP servers. Drive cross-team platform strategy, mentor engineers, own complex multi-quarter projects, and ensure reliability, performance, and operational excellence across microservices and event-driven systems.

Lead technical vision and execution for enterprise-scale AI, automation, and data initiatives. Architect scalable, secure AI systems and data pipelines, mentor engineers, drive cross-functional alignment, and deliver high-impact production solutions that improve productivity and business outcomes.

As a Data Scientist - AI Engineer, you will apply machine learning and AI to analyze revenue data, forecast trends, and enhance sales strategies, directly influencing business decisions.

As a Principal AI Engineer, you'll design AI systems for healthcare, collaborate with cross-functional teams, and enhance care delivery workflows.