AI/Machine Learning Data Engineer

Acosta Group is seeking a highly skilled and adaptable AI/ML Data Engineer to design, develop, deploy, and support AI-powered solutions that enhance Acosta’s internal operations and decision-making capabilities. This role combines deep technical expertise with a strong focus on scalability, reliability, and integration across enterprise platforms such as Azure AI, Power Platform, and Copilot Studio.

The ideal candidate will have hands-on experience with cloud platforms (preferably Azure), agentic frameworks (e.g., LangChain), Large Language Models (LLMs), and generative AI techniques including fine-tuning and Retrieval-Augmented Generation (RAG). Proficiency in Python and SQL is essential, along with a solid understanding of vector databases, semantic search, and dimensional data modeling. Experience with Databricks, serverless deployments (e.g., Azure Functions), containerization (Docker/Kubernetes), and CI/CD pipelines using Azure DevOps is highly valued.

Beyond technical implementation, the AI Engineer will provide second- and third-level support, mentor business users and citizen developers, and collaborate with cross-functional teams to embed AI into business-critical workflows. The role also supports Acosta’s broader AI initiatives by enabling infrastructure readiness, contributing to the AI Center of Excellence, and integrating intelligent automation tools across the enterprise.

This is a hybrid role based in our office environment in either Jacksonville, FL, Lewisville, TX or Mississauga/Toronto, ON . Candidates will be expected to work as much as 3 days per week onsite depending on proximity to corporate hubs.

Essential Functions of this Position

• Design, develop, and deploy AI/ML models and intelligent automation solutions that support internal business operations and strategic initiatives
• API Development & Integration: Ability to build and integrate REST/GraphQL APIs to serve AI/ML models.
• Vectorization & Embeddings: Expertise in vector databases and semantic search.
• Collaborate with cross-functional teams to identify, scope, and implement AI use cases using tools such as Azure AI, Power Platform AI Builder, and Copilot Studio
• Integrate AI capabilities into enterprise applications and workflows, including Power Apps, Power Automate, and Microsoft 365
• Monitor and maintain AI solutions in production, ensuring performance, reliability, and responsible AI practices
• Provide second- and third-level support for AI-related incidents, enhancements, and deployments
• Partner with infrastructure and security teams to ensure readiness and compliance for AI workloads
• Contributes to the development of reusable AI components, templates, and frameworks to accelerate adoption
• Mentor and support business users and citizen developers in building and scaling AI-powered solutions
• Participate in the evaluation of new AI tools, platforms, and methodologies to support innovation and continuous improvement
• Document solution architectures, workflows, and best practices to support knowledge sharing and operational continuity
• Support the AI Center of Excellence by contributing to governance, enablement, and enterprise-wide AI strategy
• Maintain and enforce change control processes.
• Assist in developing and maintaining operational standards and best practices.
• Leverage AI and automation tools for proactive monitoring, anomaly detection, and incident response.
• Collaborate with AI Solutions Engineers and the AI Center of Excellence to support infrastructure for AI workloads and pilot initiatives.
• Ensure infrastructure readiness for hybrid cloud and AI platforms (e.g., Azure ML, VMware Private AI, NVIDIA AI Enterprise).
• Perform other duties as required and/or assigned.

Applicants must be legally authorized to work in the United States and/or Canada without the current or future need for employer-sponsored work authorization.

Minimum Education and Work Experience

• Bachelor’s Degree in Technology Industry is preferred or equivalent work experience
• High School Diploma/ GED is required
• Two (2) or more years of professional experience in Machine Learning, Data Science, or Software Engineering.
• Microsoft Exam AI-102: Designing and Implementing an Azure AI Solutions (preferred).

Knowledge, Skills, and Abilities Requirements

• Programming: Proficiency in Python (must) and SQL for data manipulation, querying, and automation.
• Data Warehousing: Solid understanding of data warehouse concepts, including dimensional modeling (fact and dimension tables).
• Agentic Frameworks: Knowledge of AI agent frameworks and orchestration (e.g., LangChain).
• LLMs & Generative AI: Strong understanding of Large Language Models, fine-tuning, and RAG pipelines.
• Knowledge of machine learning fundamentals, including supervised and unsupervised learning, NLP, and generative AI
• Familiarity with MLOps practices and tools for model lifecycle management and monitoring
• Understanding of responsible AI principles