AI Engineer

Title – Fulltime AI Engineer
Location - onsite 5 days a week in NW Houston TX

How success is defined: 

• Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems, and natural language interfaces. 

• Integrate AI and machine learning capabilities into enterprise applications and platforms using services such as Azure AI, OpenAI, and similar technologies. 

• Architect and build reusable AI frameworks, components, and services to enable enterprise-wide scalability, standardization, and rapid deployment. 

• Partner with data engineering teams to develop ML-ready datasets, feature pipelines, and robust data foundations that support advanced analytics and AI use cases. 

• Leverage enterprise data platforms (e.g., Azure, Fabric, Synapse) to design and execute scalable, high-performance AI workloads. 

• Embed AI-driven insights and predictive analytics into BI solutions (e.g., Power BI, Datamarts) and integrate outputs into dashboards, semantic models, and reporting layers. 

• Ensure alignment of AI and analytics solutions with enterprise KPIs, reporting standards, and data governance frameworks across ERP, CRM, and operational systems. 

• Develop intelligent automation and decisioning systems that combine machine learning with rule-based logic to enable proactive monitoring, anomaly detection, and self-healing capabilities. 

• Establish and enforce Responsible AI practices, including model transparency, explainability, monitoring, and ethical use of data and algorithms. 

• Ensure compliance with enterprise data governance, security, and regulatory requirements, maintaining auditability and integrity of AI models and outputs. 

• Translate business requirements into AI-enabled solutions by partnering cross-functionally with Finance, Sales, Operations, and other stakeholders to prioritize high-value use cases. 

• Communicate AI solutions and insights to technical and non-technical audiences and support user enablement, training, and adoption of AI-driven analytics tools. 

• Works effectively with others in a team environment to accomplish organizational goals and to identify and resolve problems. 

• Exhibits and adheres to the established Visual Comfort Company Values. 

• Must demonstrate commitment, dependability, punctuality, and adherence to agreed-upon schedule while being present in the workplace to effectively collaborate and communicate amongst co-workers and teams. 

What you will bring: 

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field; equivalent combinations of education and experience will be considered. 

• 4-7 years of experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade AI and data solutions in enterprise environments. 

• 4-7 years of hands-on programming experience with Python and SQL, including building, testing, and deploying data-driven applications and models. 

• 4-7 years of experience with machine learning frameworks and model lifecycle management, including training, validation, deployment, and monitoring. 

• Demonstrated experience integrating AI/ML solutions into enterprise applications and reporting platforms, including BI tools such as Power BI or similar visualization technologies. 

• 4-7 years of experience working with cloud data and AI platforms (Azure, AWS, or similar), including services such as Azure AI, Azure ML, OpenAI, Synapse, or Fabric. 

• Strong understanding of data modeling (including dimensional modeling), semantic layers, and enterprise reporting structures. 

• Experience designing and supporting ETL/ELT pipelines and collaborating with data engineering teams to enable scalable AI and analytics solutions. 

• Strong analytical, organizational, and problem-solving skills, with high attention to detail and the ability to manage multiple priorities in a fast-paced, evolving environment. 

• Ability to translate complex business requirements into scalable, high-impact technical solutions and align AI initiatives to business outcomes across functions such as Finance, Sales, and Operations. 

• Effective communication and collaboration skills, including the ability to clearly convey technical concepts across multiple channels (e.g., email, chat, presentations) and work independently or as part of cross-functional teams. 

• Experience with enterprise systems (e.g., ERP platforms such as D365 or JD Edwards) and industry domains such as retail, manufacturing, or supply chain analytics is nice to have not required. 

• Experience developing AI copilots, chatbots, or enterprise AI agents is preferred. 

• Microsoft certifications in Azure AI, Data, or Power BI are a plus. 

• Ability to work a flexible schedule to support business needs, including occasional early mornings, evenings, or weekends as required. 

Some highlight benefits 

• Work-Life Balance: Monday – Friday, 8:00am – 5:00pm, Domestic Travel 25% 

• Training & Development:A comprehensive and structured training program, complemented by ongoing education and opportunities for career advancement. 

• Paid Time Off:Generous vacation accrual and paid time off policies. 

• Holidays:7 paid holidays per year, in addition to 2 floating holidays. 

• Compensation:Competitive compensation plan 

• Health Benefits:Visual Comfort covers the majority of employee medical premiums, and offers competitive vision and dental coverage available starting the first of the month following your start date. 

• Insurance:Company-provided life insurance and short-term disability coverage. 

• Retirement:401(k) plan with company matching up to 4%, available beginning the first of the month following your hire date. 

Important 

To ensure we are on the same page and to help with your search efforts, I wanted to share a few additional details about ideal candidate: 

• Strong communication skills:The ability to clearly explain AI/ML concepts to key stakeholders in understandable language is essential. We need someone who can communicate confidently and effectively with both technical and nontechnical audiences. 

• AI/ML and Data Science Experience:we are prioritizing candidates with a more extensive background in AI/ML and/or data science. 

• Depth of Experience:AI/ML experience targeting 4–7 years of relevant experience. This is key because the hiring manager needs someone who can step in and contribute independently with minimal supervision. 

• ML Frameworks and Model Lifecycle:need to see the depth of experience candidate has across model training, validation, deployment, and monitoring.