Artificial Intelligence Jobs in Westminster, CO

Leads financial strategy and operations for the Arvada site, overseeing budgeting, forecasting, reporting, annual planning, standards and rate setting. Develops strategies to improve profitability and growth, ensures regulatory and company-policy compliance, and partners with cross-functional teams on operational improvement and financial analytics. Uses AI and financial systems to strengthen processes, while leading and developing the site finance team.

Leads enterprise AI research and development strategy, combining classical and generative AI into production-grade platforms, agentic systems, and customer products. Builds and scales teams of applied scientists and engineers, advances hybrid AI architectures, establishes experimentation and evaluation practices, and embeds responsible AI principles. Partners with senior leaders, academia, and industry to commercialize research and deliver measurable business impact.

Partners with executive leaders to diagnose organizational needs, guide change, and improve culture and effectiveness. Leads employee engagement, performance management, workforce planning, succession management, talent development, and organizational change initiatives. Advises on AI tools for talent acquisition, predictive turnover modeling, and employee experience. Ensures HR policies comply with employment legislation while translating business plans into talent strategies.

Leads and develops a SaaS application support team, overseeing queue operations, metrics, escalations, and customer service delivery. Implements AI agents and large language models to automate support workflows and improve efficiency. Partners with Engineering, Product, and Sales to advocate for customers and drive product enhancements. Analyzes support trends, optimizes processes, and establishes service standards while fostering continuous team development.

Lead the AI Center of Excellence’s architecture and execution for enterprise business systems. Design and deploy generative AI, machine learning, agentic, automation, and RAG solutions across Google Cloud, Oracle, and Salesforce ecosystems. Establish ModelOps, security, privacy, governance, observability, and responsible AI standards. Guide integrations, pilots, production rollouts, cost optimization, and technical decision-making while mentoring AI developers and data engineers and communicating with executive stakeholders.

Lead an agile engineering pod developing secure, scalable AI-powered production features. Responsibilities include directing AI coding agents, establishing architectural guardrails, transforming prototypes into reliable software, managing CI/CD and evaluation infrastructure, and leading hiring, mentoring, performance coaching, and career development. The role requires technical architecture expertise across C#/.NET, front-end frameworks, databases, APIs, ETL, and ethical AI practices.

Build and operate secure, scalable platform infrastructure for AI-driven applications across cloud, on-premises, and edge environments. Own SRE practices, CI/CD, deployment automation, observability, performance optimization, incident response, and reliability improvements. Develop Python-based internal tools, partner with software teams on production readiness, and support customer-site installations and lifecycle operations. The role also emphasizes security, compliance, developer productivity, and distributed-system troubleshooting.

Build production-grade AI applications using computer vision, multimodal AI, geospatial data, drone imagery, 3D environments, and sensor data. Develop Python services, APIs, data pipelines, and optimized models with PyTorch and ONNX. Support drone inspection, mapping, perception, and autonomy workflows while contributing to architecture, testing, CI/CD, deployment, and reliability. Collaborate with engineers and domain experts to prototype, evaluate, and productionize emerging AI techniques.

Designs, develops, and deploys AI-powered tools, agents, workflows, and enterprise applications. Partners with business and operations stakeholders to identify automation opportunities, translate requirements into scalable solutions, and integrate LLMs, APIs, cloud AI services, and enterprise technologies. Establishes prompt engineering, validation, governance, monitoring, and responsible AI practices while creating user interfaces and dashboards. Evaluates emerging technologies and contributes to AI architecture, strategy, and innovation initiatives.

Designs, develops, and deploys AI-powered applications, agents, workflows, and automation solutions that improve business operations. Partners with stakeholders to translate operational challenges into scalable AI systems, integrates LLMs and cloud AI services, establishes prompt engineering and governance practices, and creates user-friendly tools and dashboards. The role also evaluates emerging technologies and contributes to AI architecture, strategy, and innovation initiatives.

Lead technical onboarding, implementation, and post-sales support for enterprise customers deploying AI cybersecurity solutions. Manage implementation plans, milestones, risks, technical relationships, and issue triage while coordinating with Sales, Engineering, Services, Product, and Support. Develop repeatable technical documentation and advocate for customer feedback. The role requires extensive post-sales technical experience, AI systems deployment expertise, enterprise infrastructure knowledge, and the ability to manage complex deployments in a high-growth environment.

Build AI applications, agents, integrations, and automated workflows that transform technical information into customer documentation. Partner with the Documentation team to use LLMs, agentic AI, and automation to improve content creation, maintenance, publishing, and delivery. Reduce manual effort, increase access to technical knowledge, and identify additional customer-facing workflows where AI can improve efficiency and experience.

Develop spatial AI and perception systems for autonomous mobile robots operating in dynamic warehouses and yards. Train and evaluate models using real multimodal fleet data, improve 3D scene representations and state estimation, and develop evaluation methods. Take research concepts from literature through on-vehicle validation and productionization, collaborating with software and test engineering on data, annotation, calibration, monitoring, and simulation infrastructure.

The Principal Cloud DevOps Engineer is responsible for deploying and maintaining IFIaaS applications in hybrid cloud environments, ensuring reliability, managing CI/CD pipelines, and providing on-call support.