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Ai Monitoring Jobs in Colorado (NOW HIRING)

Google AI Lead Architect

Denver, CO · On-site

$56.75 - $78/hr

Google AI Lead Architect/AI & Engineering: Join our AI & Engineering team in transforming ... Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis ...

AI Ops Engineer III

Denver, CO · On-site

$54.25 - $74.25/hr

Deploy, monitor, and optimize AI agents and supporting infrastructure within Google Cloud Platform (Google Cloud Platform) environments * Collaborate with data scientists, analysts, and business ...

AI Engineer

Denver, CO

$110K - $150K/yr

Instrument AI solutions for telemetry, reliability, performance monitoring, and cost control. * Provide technical support and troubleshooting for deployed AI solutions. * Identify implementation ...

Instrument AI solutions for telemetry, reliability, performance monitoring, and cost control. * Provide technical support and troubleshooting for deployed AI solutions. * Identify implementation ...

This is an engineering\-focused role for someone who can move beyond AI strategy and experimentation and actually build, integrate, test, secure, monitor, and operate AI\-powered applications and ...

New

Monitor and troubleshoot AI agent behavior, diagnosing issues across conversation flows and escalating technical issues as needed. * Implement and iterate on dynamic response content, including ...

... monitoring). * 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls)

Sr AI/ML Engineer

Englewood, CO · On-site

$102K - $179K/yr

You will lead the full AI lifecycle from experimentation through production, developing both ... Implement monitoring, drift detection, retraining pipelines, and model lifecycle management ...

... monitored, auditable architecture. * Workflow Automation Design end-to-end AI workflows spanning client discovery, investment research synthesis, portfolio construction and optimization, and ...

Responsibilities : • Design, build, and deploy end-to-end GenAI solutions and agentic solutions, including model lifecycle management, evaluation, deployment, and monitoring. • Partner with ML/AI ...

AI Engineering Lead

Denver, CO · On-site

$147 - $220/hr

Establish monitoring and observability across AI systems (performance, usage, cost, latency, failure modes) * Implement modern engineering practices including CI/CD, versioning, rollback strategies ...

New

Design, build, and deploy agentic AI workflows that autonomously execute multi-step business ... Build and maintain agent monitoring frameworks to track performance, detect failures, and trigger ...

AI Solutions Analyst

Greeley, CO · On-site

$90K - $127K/yr

Agentic AI Design & Automation - 50% * Design, build, and deploy agentic AI workflows that ... Build and maintain agent monitoring frameworks to track performance, detect failures, and trigger ...

AI Engineering Lead

Denver, CO · On-site +1

$105K - $139K/yr

... monitoring and observability across AI systems (performance, usage, cost, latency, failure modes) • Implement modern engineering practices including CI/CD, versioning, rollback strategies, and ...

Showing results 21-40

Ai Monitoring information

What is AI monitoring?

AI monitoring refers to the process of continuously observing and analyzing artificial intelligence systems to ensure they operate as intended. This includes tracking performance, detecting anomalies, ensuring compliance with ethical guidelines, and identifying potential biases or errors. Effective AI monitoring helps organizations maintain transparency, improve system reliability, and ensure that AI models make fair and accurate decisions. It is essential in applications where AI impacts critical business or societal outcomes.

What are some common challenges faced by professionals in AI monitoring roles, and how can they be addressed?

Professionals in AI Monitoring often encounter challenges such as managing large volumes of data, identifying and responding to atypical model behavior, and ensuring compliance with ethical and regulatory standards. Staying updated on the latest AI trends and best practices, utilizing robust monitoring tools, and collaborating closely with data scientists and engineers can help address these challenges. Regular training and open communication within cross-functional teams are also essential to maintain effective oversight and quickly mitigate potential issues.

What are the key skills and qualifications needed to thrive as an AI monitoring specialist, and why are they important?

To thrive as an AI Monitoring Specialist, you need a solid understanding of data analysis, machine learning concepts, and system monitoring, often supported by a degree in computer science or a related field. Familiarity with monitoring platforms like Datadog, Prometheus, or Splunk, as well as experience with scripting languages and AI model management tools, is typically required. Attention to detail, critical thinking, and strong communication skills help specialists identify issues quickly and collaborate with technical teams. These skills and qualities are crucial for ensuring AI systems operate reliably, securely, and efficiently in real-world applications.

What is the difference between Ai Monitoring vs Data Analyst?

AspectAi MonitoringData Analyst
Required CredentialsTypically requires knowledge of AI systems, programming, and data analysis toolsRequires statistical, analytical, and data visualization skills, often with a degree in data science or related fields
Work EnvironmentOften involves monitoring AI systems in real-time, using specialized software, in tech or AI-focused companiesAnalyzes data sets, creates reports, and provides insights, working in various industries like finance, marketing, or healthcare
Employer & Industry UsageCommon in AI development firms, tech companies, and organizations deploying AI solutionsWidely used across industries for decision-making, reporting, and strategic planning

While both roles involve working with data, Ai Monitoring focuses on overseeing AI system performance and ensuring operational accuracy, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

Infographic showing various Ai Monitoring job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 1% Temporary, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Full-time

Re-posted 29 days ago


Job description

Job Summary:
D.A. Davidson Companies is an independent, employee-owned company dedicated to integrity and outstanding service. They are seeking a Mid-Level AI and Automation Engineer to develop AI capabilities within a Microsoft environment, focusing on intelligent assistants and automated workflows to transform business processes in the financial services domain.
Responsibilities:
• Design and Develop AI-Powered Workflows: Use Microsoft Copilot Studio and Power Platform (Power Automate, Power Apps) to design, build, and optimize AI assistants and automated workflows that enhance employee productivity and decision-making.
• Integrate Enterprise Data and Systems: Connect AI copilots to enterprise data sources and APIs, enabling context-rich automation (e.g. integrating Azure AI services or databases with Copilot agents for real-time information retrieval).
• Apply AI Best Practices: Implement prompt engineering techniques and fine-tune AI models or prompts to improve the relevance and accuracy of Copilot responses. Utilize Azure OpenAI or similar services to incorporate advanced language AI capabilities when needed.
• Ensure Compliance and Security: Build solutions with robust security, privacy, and compliance controls in mind, aligning with corporate policies and industry regulations (financial data protection, responsible AI use, audit logging). Work closely with governance teams to enforce security standards for AI integrations.
• DevOps and Monitoring: Develop CI/CD pipelines for deploying and updating AI agents or automation workflows, ensuring smooth rollouts and version control. Set up monitoring and telemetry dashboards to track performance, usage, and quickly address any issues.
• Collaboration and Iteration: Work in an Agile team alongside product managers, business analysts, and designers to refine requirements and user stories. Iterate on solutions based on user feedback and analytics, continuously improving the AI assistants’ effectiveness.
• Documentation and Training: Document solution designs, workflows, and configurations. Help create user guides or demo sessions to drive adoption of the new AI-powered tools among employees and stakeholders.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Software Engineering, or related field.
• 5+ years of experience in software development, automation engineering, or similar roles.
• Hands-on experience with Microsoft Power Automate and related Power Platform tools for workflow automation.
• Familiarity with M365 Copilot features or similar AI bot/agent development tools (e.g. Azure AI services, cognitive services).
• Proficiency in at least one programming or scripting language (such as Python, C#, or JavaScript) to extend and customize solutions.
• Experience building or consuming RESTful APIs and working with data integration.
• Working knowledge of Azure cloud services and AI/ML frameworks.
• Ability to deploy applications or automations in a cloud environment and integrate AI APIs (Azure OpenAI, Azure Cognitive Services, etc.).
• Experience with version control (git and Bitbucket) and continuous integration/continuous deployment (CI/CD) pipelines for software projects.
• Comfortable using tools like Azure DevOps or GitHub Actions to automate build-test-deploy processes.
• Strong analytical and problem-solving skills with a track record of delivering solutions that meet business needs.
• Excellent communication skills to work effectively with both technical and non-technical team members.
• Align efforts with other lines-of-business and functional areas, such as our partners in Operations, Finance, Wealth Management, and more.
• Commitment to maintain client confidentiality and data security.
• Communicate in a clear and service-oriented manner; use appropriate, professional language and grammar to effectively exchange ideas and information.
• Ability to proactively work with both external and internal clients; relate with others in a professional manner to accomplish work responsibilities and objectives.
• Ability to maintain regular, predictable attendance.
Preferred:
• Experience with Microsoft 365 Copilot Studio – for example, having built or managed AI copilots/agents in a production setting.
• Knowledge of designing conversation flows, topics, tools, and using Copilot’s advanced features (custom actions, agent-to-agent workflows).
• Familiarity with large language models beyond basic API usage – e.g., experience with prompt tuning, deploying LLMs, or implementing retrieval-augmented generation (RAG) pipelines with vector databases for domain-specific Q&A.
• Experience with Azure AI Foundry and Azure AI capabilities like document intelligence, computer vision, speech, and more.
• Background in financial services or wealth management technology projects.
• Understanding of industry regulatory requirements (e.g. data privacy, audit, model risk management) and how to design AI solutions that comply with them.
• Hands-on experience implementing security, compliance, and responsible AI practices in software.
• Familiarity with Microsoft’s Responsible AI guidelines, Azure Purview for data governance, or similar tools to control AI use.
• Demonstrated initiative in previous roles – maybe you introduced a new automation tool, led a pilot of an AI solution, or actively contributed to AI/automation communities.
• Microsoft certifications in Azure AI, Power Platform, or related areas would be an advantage, reflecting your commitment to staying current.
• Lots of experience working in highly-iterative development processes.
• Somebody prepared to deal with the boring and the tough.
Company:
D.A. Founded in 2002, the company is headquartered in New York, USA, with a team of 1001-5000 employees. The company is currently Late Stage.