AI Engineer I - Hybrid
Tolmar · Windsor, CO
- On site
- Full-time
- $135,000 / year
- Windsor, CO
Job highlights
- Design and deploy AI solutions in production.
- Develop agentic workflows and RAG systems.
- Collaborate with cross-functional teams.
- Ensure AI solutions are reliable and governed.
- Integrate AI into enterprise systems.
About the role
AI Engineer - Hybrid
The Applied AI Engineer will help design, develop, and deploy generative and agent-based AI solutions throughout the organization. Work centers on real-world production use cases, focusing on practical AI applications such as agentic workflows, retrieval-augmented generation (RAG), prompt engineering, and AI-driven automation. The role places a strong emphasis on moving projects from experimentation to reliable, well-governed production environments. The AI Engineer is a hands-on, builder-focused role and collaborates closely with software engineers, data engineers, product owners, and business stakeholders to integrate AI capabilities into operational workflows across Tolmar.
Essential Duties & Responsibilities
Applied AI & Agentic Solutions
- Build and enhance AI‑powered applications and agents that support real business workflows (e.g., document analysis, task delegation, knowledge retrieval, decision support).
- Implement agentic patterns such as tool‑calling, multi‑step reasoning, and workflow orchestration in collaboration with senior engineers.
- Develop and manage prompt strategies, prompt templates, and prompt evaluation techniques for reliability and reuse.
- Implement retrieval‑augmented generation (RAG) using enterprise data sources and vector databases.
Engineering & Production Readiness
- Help transition AI solutions from prototype to production, focusing on reliability, observability, and cost awareness.
- Package AI capabilities as APIs, services, or integrations consumable by other applications.
- Contribute to CI/CD pipelines and deployment patterns for AI applications (model updates, prompt changes, configuration).
- Monitor AI solutions in production and assist with troubleshooting performance, accuracy, or usability issues.
Data, Integration & Platform Collaboration
- Work with data engineers to integrate AI solutions with governed data sources (e.g., Fabric, Dataverse, SQL).
- Collaborate with platform teams on Azure‑based AI services, Copilot integrations, and Power Platform solutions.
- Support integration of AI into existing enterprise systems (ERP, content repositories, workflow tools).
Evaluation, Learning & Governance Awareness
- Participate in model and solution evaluation, including accuracy, latency, cost, and usability.
- Support testing and validation activities aligned with internal AI governance standards.
- Stay current with evolving AI tools, frameworks, and best practices and contribute ideas back to the team.
- Contribute to internal documentation, reusable patterns, and AI communities of practice.
- Perform other related duties as assigned.
Knowledge, Skills & Abilities
- Understanding of emerging standards for providing context to AI models, such as Model Context Protocol (MCP), and experience developing reusable "agent skills" to enhance model capabilities.
- Familiarity with cloud platforms (Microsoft ecosystem (Azure/Fabric) preferred).
- Strong curiosity, learning velocity, and willingness to experiment responsibly.
- Ability to communicate clearly with both technical and non‑technical partners.
- Proficiency in designing, implementing, and troubleshooting AI solutions within enterprise environments.
- Ability to analyze and interpret complex data sets, applying statistical and machine learning techniques to derive actionable insights.
- Experience with integrating AI models into business processes, workflow tools, and content management systems.
- Knowledge of data governance, privacy, and ethical considerations in AI development and deployment.
- Competency in testing, validating, and monitoring AI models for performance, reliability, and compliance.
- Skill in preparing technical documentation and creating reusable frameworks or patterns for AI projects.
- Ability to collaborate effectively with cross-functional teams, including data engineers, platform specialists, and business stakeholders.
- Adaptability to rapidly evolving AI technologies, frameworks, and industry best practices.
- Strong problem-solving and critical thinking skills, with a focus on continuous improvement and innovation.
- Demonstrated ability to manage multiple projects or tasks concurrently, prioritizing effectively to meet deadlines.
Core Values
This position is expected to operate within the framework of Tolmar’s Core Values: Center on People, Are Proactive & Agile, Act Ethically, Constantly Improve, Are Accountable.
Education & Experience
- Bachelor’s degree in business administration, science, technology, engineering, and mathematics (STEM); computer science; artificial intelligence; data science; information systems or related field; or equivalent work experience.
- Five years of IT experience, professional experience or demonstrated hands-on project work in software engineering, applied AI, Data engineering or intelligent automation.
Working Conditions
Working conditions are consistent with a normal office environment and/or remotely from home office. Some travel might be required.
Compensation And Benefits
Annual pay range $125,000 to $135,000 depending on experience. Bonus Eligible. Benefits information: https://www.tolmar.com/careers/employee-benefits. Tolmar compensation programs are focused on equitable, fair pay practices including market-based base pay and a strong benefits package. The final compensation offered may vary from the posted range based on the selected candidates qualifications and experience. Tolmar is an Equal Opportunity Employer.
Key skills/competency
- AI Engineer
- Generative AI
- Agent-based AI
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI-driven Automation
- Production Deployment
- Cloud Platforms (Azure)
- CI/CD
- Data Integration
Skills & topics
- AI Engineer
- Generative AI
- Agent-based AI
- Prompt Engineering
- RAG
- AI Automation
- Production AI
- Azure AI
- Software Engineering
- Data Engineering
How to get hired
- Tailor your resume: Highlight experience with AI engineering, generative AI, RAG, and production deployments relevant to Tolmar's needs.
- Showcase technical skills: Emphasize proficiency in AI frameworks, cloud platforms (especially Azure), and CI/CD practices in your application.
- Demonstrate collaboration: Provide examples of working with software engineers, data engineers, and business stakeholders to integrate AI solutions.
- Prepare for interviews: Be ready to discuss your experience in moving AI projects from experimentation to production and your understanding of AI governance.
- Research Tolmar's values: Align your responses with Tolmar's core values of People, Proactivity, Ethics, Improvement, and Accountability.
Technical preparation
Practice building RAG systems with enterprise data.,Develop agentic workflows using AI frameworks.,Set up CI/CD pipelines for AI models.,Familiarize with Azure AI services and tools.
Behavioral questions
Describe a complex AI project you deployed.,How do you handle AI model failures?,How do you collaborate with non-technical teams?,How do you stay updated on AI trends?
Frequently asked questions
- What are the primary responsibilities of an AI Engineer at Tolmar?
- The AI Engineer at Tolmar is responsible for designing, developing, and deploying generative and agent-based AI solutions. This includes building agentic workflows, implementing RAG, prompt engineering, and ensuring AI solutions transition smoothly from experimentation to production-ready environments.
- What technical skills are most important for the AI Engineer role at Tolmar?
- Key technical skills include proficiency in AI frameworks, generative AI, agentic patterns (tool-calling, multi-step reasoning), RAG implementation, prompt engineering and evaluation, cloud platforms (Azure preferred), and CI/CD for AI applications. Experience with data integration and enterprise systems is also crucial.
- Does Tolmar use specific cloud platforms for their AI initiatives?
- Yes, Tolmar primarily utilizes the Microsoft ecosystem, with a preference for Azure and its related AI services, Fabric, Copilot integrations, and Power Platform solutions.
- What is Tolmar's approach to AI governance for new AI Engineer hires?
- Tolmar emphasizes AI governance by requiring support for testing and validation aligned with internal AI governance standards. They also value staying current with evolving AI tools, frameworks, and best practices, contributing to documentation and AI communities of practice.
- What kind of experience is required for the AI Engineer position at Tolmar?
- A Bachelor's degree in a STEM field or equivalent work experience is required, along with five years of IT experience, professional experience, or demonstrated hands-on project work in software engineering, applied AI, data engineering, or intelligent automation.
- Can an AI Engineer at Tolmar expect to work on cutting-edge AI projects?
- Yes, the role focuses on designing, developing, and deploying generative and agent-based AI solutions for real-world production use cases, including agentic workflows, RAG, and AI-driven automation. The position encourages staying current with evolving AI tools and best practices.
- What does 'agentic solutions' mean in the context of this AI Engineer role at Tolmar?
- Agentic solutions refer to AI applications and agents that can perform tasks autonomously or semi-autonomously. This includes implementing patterns like tool-calling, multi-step reasoning, and workflow orchestration to support business processes.
- How does Tolmar support professional development for its AI Engineers?
- Tolmar encourages continuous learning by expecting employees to stay current with evolving AI tools, frameworks, and best practices, and to contribute ideas back to the team. They also foster internal AI communities of practice.