Senior AI Engineer

About Apperture Solutions

Apperture Solutions is a technology independent, professional consulting, and implementation services firm. Apperture Solutions offers Data Enablement, Production Optimization, Operations Management, and Other Value-Added Services. Apperture Solutions partners with other providers to offer customers the technologies and solutions that fit their needs.

Apperture Solutions is part of Robert E. Mason & Associates, Inc., a 100% employee-owned company that believes Associates are the foundation of both customer and company success.

What Apperture Solutions Offers Associates

• Participation in the Employee Stock Ownership Program (ESOP)
• Retirement plan, including a Safe Harbor contribution
• Medical / Dental / Vision Insurance
• Employer paid Life Insurance and Long-Term Disability Insurance
• Generous paid leave options that include vacation time, sick leave, personal leave time, R.E. Mason Way Half Day, paid Jury Duty, and paid Bereavement Leave
• Paid Parental Leave
• Paid company holidays
• Career Development Program
• Retirement and Financial Wellness program
• Employee Assistance Program (EAP)
• Alternative/Hybrid Work Schedules

General Description

The Senior AI Engineer will design, build, and deploy secure, domain-specific AI solutions for industrial operations, including agentic applications, retrieval-augmented generation (RAG), machine learning services, and workflow co-pilots. This role translates complex manufacturing and engineering requirements into practical, supportable products that connect operational data with modern AI capabilities across edge, cloud, and hybrid environments.

Specific Responsibilities

• Lead the design and delivery of production-grade AI applications, including LLM agents, RAG systems, workflow co-pilots, and predictive or optimization services.
• Translate manufacturing workflows, operating constraints, and user needs into well-scoped technical solutions in partnership with operations, engineering, OT, IT, cybersecurity, and business stakeholders.
• Design agent architectures using frameworks such as LangChain or LangGraph, including supervisor-worker patterns, REST or Model Context Protocol (MCP) interfaces, governed tools, and appropriate human approval points.
• Develop enterprise retrieval solutions using embeddings, vector stores, semantic search, knowledge graphs, and structured operational content such as SOPs, logs, maintenance records, and engineering documentation.
• Use contemporary AI-assisted development tools to accelerate delivery, supported by evaluation datasets, test harnesses, guardrails, monitoring, and independent review of model behavior, generated code, and agent recommendations.
• Design agent-ready data products that route requests appropriately across live edge data, hot time-series stores, and historical lakehouse data.
• Integrate AI solutions with industrial and enterprise platforms, including OPC UA, MQTT/Sparkplug B, Unified Namespace architectures, SCADA/DCS data, Power BI, SharePoint, and custom applications.
• Partner with data engineering teams on schema-versioned data contracts, contextualization, validation, and streaming integrations across Azure Event Hubs, Azure Data Explorer, Databricks/Delta Lake, and ADLS Gen2.
• Package and operate solutions as secure, containerized services for cloud, edge, on-premises, or regulated deployment environments; contribute to CI/CD, observability, and operational support.
• Frame ambiguous industrial problems, evaluate alternative approaches, and advance promising concepts from rapid prototype to maintainable production capability.
• Document architecture, design decisions, limitations, validation evidence, data contracts, workflows, and compliance touchpoints; provide technical leadership through reviews, mentoring, and cross-team handoffs.

Required Competencies

• Python software engineering: Strong skills and experience building APIs, data services, and AI/ML applications using frameworks such as FastAPI, PyTorch, LangChain, or LangGraph.
• LLM-based systems: Hands-on experience building or integrating LLM-based systems using commercial or open-source models and applying prompt engineering, structured outputs, tool calling, and model orchestration.
• RAG architecture: Practical knowledge of RAG architecture, embedding models, vector databases, semantic search, and techniques for evaluating retrieval and generation quality.
• Critical evaluation: Demonstrated ability to assess AI-assisted outputs for correctness, security, maintainability, performance, and fitness for use rather than relying on generated results at face value.
• Production systems: Experience designing reliable production systems with automated testing, version control, CI/CD, logging, monitoring, containerization, and secure deployment across Azure, edge, or hybrid environments.
• Operational workflows: Ability to understand process, manufacturing, or other operational workflows and convert them into clear data, software, and AI requirements.
• Technical judgment: Sound technical judgment, curiosity, and resourcefulness when working through open-ended problems, incomplete information, and competing design options; ability to explain tradeoffs and risks to engineering and operational audiences.
• Collaboration: Ability to work independently, collaborate across disciplines, manage priorities, and maintain attention to detail while supporting customer outcomes, responsible AI practices, and continuous learning.

Required Education & Experience

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent relevant experience.
• Five or more years of professional experience in AI/ML, software engineering, data science, or a closely related discipline, including ownership of production solutions.
• Experience taking at least one AI or ML capability from problem definition through deployment, validation, monitoring, and operational support.
• Experience working within software delivery practices that include Git, code review, automated testing, and agile or flow-based execution.

Preferred Experience / Competencies

• Experience with industrial data and controls, including OPC UA, MQTT/Sparkplug B, SCADA/DCS, PLCs, industrial historians, Unified Namespace patterns, or ISA-95/ISA-88 contextualization.
• Experience with Azure data services such as Event Hubs, Azure Data Explorer/KQL, Databricks, Delta Lake, Unity Catalog, Structured Streaming, or ADLS Gen2.
• Experience designing schema-versioned data contracts, validation pipelines, time-series data products, or lakehouse medallion architectures.
• Familiarity with Model Context Protocol (MCP), governed agent tool design, multi-agent orchestration, or human-in-the-loop workflows.
• Domain exposure in power generation, life sciences, batch manufacturing, or another regulated process industry, including reliability, maintenance, optimization, or operational analytics use cases.
• Experience with architecture decision records, technical standards, and cross-team contract-based delivery.

Physical Requirements

• Standing
• Walking
• Sitting
• Kneeling
• Reaching Overhead
• Climbing
• Pushing and Pulling
• Lifting - 50 pounds
• Using a Computer
• Using a Telephone
• Driving

Additional Information

Apperture Solutions is a federal contractor and, as such, is required to solicit the disability status and protected veteran status of candidates. You are required to answer self-identification questions as part of your application process. These questions are part of Apperture Solution's Affirmative Action Plan and the completion of these questions will not have any effect on any consideration of your application materials.

In compliance with the ADA Amendments Act (ADAAA), if you have a disability and need to request an accommodation in order to apply for a position with Apperture Solutions, please call our office at (704) 375-4465.

This is a drug-free workplace. Employment is contingent upon the successful completion of any required pre-employment and, if applicable, ongoing drug testing, including testing mandated by customer site access requirements.