Physical AI Forward Deployed Engineer

BiaTech Corporation•Tulsa, OK

14d•Hybrid

About The Position

BiaTech develops Physical AI solutions that combine industrial data, physics-informed models, edge computing, digital twins, and conversational AI to help frontline teams make better operational decisions. We are seeking a Tulsa-based Forward Deployed Engineer to own the technical delivery of customer applications, from understanding an operating problem through deployment, validation, and sustained use. You will work alongside operators, maintenance personnel, engineers, and business leaders, connecting their operating reality with BiaTech's product and engineering teams. You will bring industrial judgment, practical engineering and data skills, and the ability to earn customer trust. We will train you on BiaTech's platform. Prior AI specialization is welcome; demonstrated ability to troubleshoot systems and turn technical work into useful operating results is essential.

Requirements

Bachelor's degree or higher in engineering, physics, computer science, or a related technical discipline, or equivalent relevant technical experience.
Five or more years of relevant experience in industrial engineering, automation, applications engineering, field service, industrial software, or technical customer delivery, including direct work with operating teams.
Practical understanding of rotating equipment, fluid systems, instrumentation, and controls, with evidence of troubleshooting real equipment or operational systems.
Hands-on data analysis and scripting ability, using Python or a comparable language, and experience configuring or integrating technical systems. You can investigate logs, test assumptions, and document a reproducible solution.
A record of taking a technical project from an ambiguous customer problem to a working solution, with clear communication, sound judgment, and reliable follow-through.
A safety-first approach that follows customer HSE requirements, site procedures, and required PPE, together with the ability to work independently, adapt priorities, and travel as described above.

Nice To Haves

Upstream energy experience is strongly preferred, including drilling, production, artificial lift, pipelines, or field facilities.
Experience in other process industries is also relevant.
Industrial data systems such as SCADA and historians.
Edge computing or robotics.
Commissioning.
Process optimization.
Applied simulation, digital twins, or physics-informed AI.
A graduate degree or research background is welcome but not required.

Responsibilities

Define the application. Work with customers to understand equipment, workflows, failure modes, and priorities. Agree on the use case, baseline, data requirements, operating constraints, and measurable acceptance criteria.
Own deployment. Develop and execute the technical delivery plan, coordinate customer and BiaTech contributors, track dependencies and risks, and carry the application through testing, commissioning, acceptance, and operational handoff.
Work hands-on in the field. Configure and troubleshoot sensing and edge systems, connectivity, and hardware integration. Lead site commissioning, including robotic applications where relevant, with support from engineering specialists and customer personnel.
Make data usable. Check sensor tags, units, timestamps, data quality, and operating context. Use scripts, APIs, configuration tools, and logs to analyze data, connect systems, and isolate problems across hardware, networks, and software.
Validate performance. Work with domain and modeling specialists to compare outputs with field measurements, physical constraints, and agreed criteria. Identify uncertainty, failure conditions, and limits on use; document and escalate gaps before acceptance.
Enable customer adoption. Demonstrate applications, train users, document operating and support procedures, and follow up on usage and results. Explain findings clearly to operators, engineers, and business leaders.
Improve the product. Turn recurring field issues into actionable requirements, reproducible bug reports, reusable integrations, diagnostic tools, and deployment playbooks. Partner with core engineering to incorporate improvements into the platform.
Support customer growth. Help scope pilots and follow-on applications, contribute to proposals and technical demonstrations, and identify expansion opportunities grounded in delivered value. Keep commitments aligned with product capability and delivery capacity.