Top Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

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.

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.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

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.

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.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Design, build, and ship production LLM-powered features for Gusto Retirement. Implement and integrate LLMs (RAG, agents, prompting, tool loops), make pragmatic architecture decisions, collaborate with product, design, and engineering, write reliable well-tested code, and drive end-to-end execution and iteration.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead the creation of innovative AI solutions for healthcare systems, serve as a trusted advisor, foster collaboration, and drive operational excellence while managing complex challenges in healthcare AI.

As a Lead Software Engineer, you'll design and develop GenAI platforms, integrate LLMs, mentor engineers, and solve technical challenges for scalable solutions.

Build scalable Databricks/Spark data pipelines, implement automated GitLab CI/CD workflows, apply SOLID engineering and testing to ensure pipeline reliability, integrate AI/ML and NLP tools, mentor peers, and operationalize models in AWS production environments.

As a Senior AI/Data Engineer, you will design and maintain scalable data and AI infrastructures, partnering with cross-functional teams to deliver reliable data systems and support AI-driven business capabilities.

The role involves engineering self-healing AI systems with high observability, developing RAG pipelines, and automating incident resolution using Python and Ansible.

The Senior AI Platform Engineer will lead technical onboarding to the Databricks platform, connect data sources, and implement governance and cost management for AI use cases.

Act as the technical presales lead for AI agent and cloud identity security across North America: scope engagements, design and run POCs and architectures across AWS/Azure/GCP, secure non-human and machine identities, create repeatable technical assets, and partner with account teams to close deals.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.