Top Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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.

Design, develop, and deploy AI solutions focusing on Generative AI and autonomous systems. Collaborate with teams to optimize AI pipelines and drive innovation.

Lead the technical evolution of software development by embedding AI into the workflow, designing intelligent ecosystems, and enhancing developer productivity.

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

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.

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

The role involves architecting and maintaining marketing databases, implementing data infrastructure for AI/ML, managing data pipelines, and collaborating with stakeholders to develop data-driven solutions.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Lead the architecture and reliability of AI-driven product applications, ensuring security, performance, and facilitating rapid prototyping and shipping. Work closely with a cross-functional team to solve user problems and translate business needs into technical solutions.

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.

Design and build core services for AI products, implement compliance guardrails, debug fullstack issues, and participate in code reviews.

Design and implement automations and AI integrations within HR technology, focusing on systems like Moveworks and Workday HCM. Collaborate with stakeholders to ensure technical alignment with HR goals.

The Staff Software Engineer will architect and code backend services and ML models, integrate systems, ensure quality, and mentor engineers in the AI & Strategy Engineering team.

Collaborate as a trusted engineering lead to design and build AI agents, develop across the full web technology stack, and enhance existing products in a Scrum Agile environment.

The Senior Applied AI Engineer will drive AI innovation, design pilots, enhance AI patterns, develop architectures in AWS, and communicate results effectively.

Design, develop, and productionize applied AI systems (RAG, LLM integrations, orchestration, agentic workflows). Ensure safe, reliable outputs with guardrails and monitoring, prototype and scale solutions, mentor engineers, collaborate cross-functionally, run experiments, and maintain testing, documentation, and production support.

Design, build, and operate production-grade LLM systems and multi-agent AI workflows. Own prompt architecture, RAG pipelines, cloud-native AI infrastructure, monitoring, and reliability to deliver scalable member-facing and operational solutions.

Design, build, and productionize Generative AI applications (document intelligence, RAG, semantic search). Implement LLM fine-tuning, vector search, agentic workflows, and MLOps on GCP; collaborate with clients to translate requirements into scalable, reliable AI services.

Develop and deliver AI-driven observability features, collaborate with cross-functional teams, and iterate rapidly to enhance user incident response capabilities.

Develop AI agents leveraging large language models, integrate external tools, and ensure production-ready AI features while collaborating across teams.