AI Automation Engineer

Hyper•Richmond, VA

21h•Hybrid

About The Position

The AI Automation Engineer at Hyper Solutions plays a key role in designing and deploying AI-powered automation systems that improve how the business operates across sales, operations, supply chain, and customer-facing workflows. This position focuses on transforming manual processes into intelligent, scalable systems using machine learning, generative AI, and automation frameworks. This role operates at the intersection of data science, software engineering, and operational improvement. You will build and deploy automation pipelines, integrate AI capabilities into core business systems, and deliver measurable impact through efficiency gains, improved decision-making, and enhanced user experiences. This position is well-suited for an engineer who enjoys applying AI and automation to real-world business problems, thrives in ambiguity, and is comfortable owning solutions from discovery through production deployment.

Requirements

3+ years of experience in data science, machine learning, or automation engineering roles
Strong proficiency in Python for data processing, model development, and automation workflows
Experience building and deploying machine learning or AI-driven systems in production environments
Hands-on experience with LLMs, prompt engineering, or generative AI frameworks
Experience designing and implementing data pipelines and ETL processes
Familiarity with MLOps practices including model versioning, deployment, and monitoring
Experience integrating with enterprise systems such as ERP, CRM, or similar platforms
Ability to take projects from initial concept through deployment and production support

Nice To Haves

Experience with agent frameworks such as LangChain, AutoGen, or similar
Familiarity with process mining tools or workflow analysis platforms
Experience working with enterprise BI tools such as Tableau or Power BI
Exposure to manufacturing, industrial, or data center environments
Experience designing internal AI training or upskilling programs
Familiarity with low-code or no-code automation platforms

Responsibilities

Analyze business processes across sales, operations, and supply chain to identify automation opportunities with measurable impact
Design, build, and deploy AI-powered automation solutions across internal and customer-facing workflows
Own the full lifecycle of automation systems including data preparation, model development, deployment, and monitoring
Develop and maintain LLM-based pipelines including prompt engineering, RAG workflows, and agent orchestration
Build integrations across enterprise systems such as ERP, PLM, CRM, and service platforms to enable AI-driven workflows
Design and implement ETL pipelines to support data-driven automation and decision systems
Apply appropriate tools and techniques including machine learning, generative AI, and process automation based on problem context
Deploy process mining capabilities to improve visibility into workflows and identify automation opportunities
Define and track automation KPIs such as cycle time reduction, error rate, and operational efficiency improvements
Translate business requirements into scoped automation solutions with clear success criteria
Evaluate and recommend tools, platforms, and technologies to expand Hyper’s automation capabilities
Contribute to building a scalable automation framework across business units
Partner with stakeholders to embed automation outputs into existing tools and workflows
Develop and deliver internal AI training programs to improve organizational adoption and capability
Maintain documentation for models, workflows, and automation systems