Top Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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 ship production-grade agentic AI workflows using LangGraph, Temporal, and Pydantic. Implement AI observability with LangFuse, set AI engineering standards (RAG, prompt management, tool-calling), benchmark LLMs, deploy cloud AI (containerization, cost management), and mentor engineers while supporting enterprise SLA, security, and compliance needs.

As a GTM AI Engineer, design and execute AI-driven workflows for Superhuman's go-to-market stack, improving automation in sales processes and team collaboration.

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.

Design and implement AI capabilities, transition prototypes to production, build agent workflows, optimize data retrieval, and automate evaluation processes.

Use advanced analytics, statistical techniques, and machine learning to extract insights from large datasets. Design data solutions and pipelines, build predictive models (R, MATLAB), and apply TensorFlow and Scikit-Learn for deep learning and NLP. Collaborate with teams and clients, deliver quality work, and adhere to firm standards.

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.

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 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.

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.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

Design, build, and deploy LLM-powered applications, collaborating with Data Science teams to ensure agent systems operate reliably in production. Handle full lifecycle from prototype to production, integrating APIs and managing workflows.

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

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.

The Applied AI Developer will design and develop AI applications, build infrastructure for agentic AI systems, integrate APIs, and collaborate with stakeholders on AI solutions.

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

The ERP AI Engineer - Manager at PwC leads teams in AI/ML engineering, manages client relationships, and designs AI solutions, all while mentoring team members and addressing complex business challenges.

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.

As a Principal AI Engineer, you'll design production-grade systems integrating generative AI in mental healthcare, overseeing architecture and applied research.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

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.

Develop and build tools using AWS technologies, create Gen AI utilities, improve quality assurance practices, and collaborate with a global team.

Design, build, and operate Jellyfish's Databricks Lakehouse and data/AI platform. Build ingestion, transformation, and delivery pipelines; govern data with Unity Catalog; enable BI, agentic analytics, metadata, lineage, and observability. Provide technical leadership, set architecture and standards, mentor peers, and collaborate with cross-functional stakeholders to make Databricks the foundation for analytics and AI.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.