Artificial Intelligence Jobs in Westminster, CO

Develop and maintain AI-driven autonomous planning, scheduling, and optimization systems for Earth observation satellite operations. Build reinforcement learning algorithms, simulation and evaluation environments, and multi-objective optimization pipelines for satellite constellation tasking. Collaborate with aerospace engineers, mission operators, software engineers, and product teams to translate mission requirements into deployable systems. The role requires strong Java and Spring Boot experience, software engineering fundamentals, and machine learning or optimization expertise.

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.

Build and integrate secure AI assistants and chatbots into geospatial intelligence and mission-support applications. Develop LLM workflows using RAG, prompt orchestration, tool calling, and conversational context; connect AI services to enterprise data sources and APIs; and enforce access controls, provenance, auditing, and safety measures. Deploy and operate services in Kubernetes and OpenShift, including classified or disconnected environments, while evaluating AI quality, security, latency, and usability.

Manage a portfolio of SaaS customers in the construction technology sector, driving adoption, retention, and measurable business outcomes. Develop customer success plans, use data and AI insights to identify risks and opportunities, lead value-focused business reviews, and collaborate cross-functionally to improve customer health and lifecycle outcomes.

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.

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.

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.

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.

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.