Top Remote Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

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 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.

Integrate and fine-tune existing AI models into product features, build evaluation frameworks and observability for production AI, collaborate with data science and engineering, and develop AI-powered application features using Python to improve user experience.

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.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

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.

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.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.