Forward Deployed Engineer – Advanced Manufacturing

In this position... While we leverage industry-standard platforms for core ERP, CRM, MES, quality, and warehouse capabilities, our highest-value problems live at the manufacturing edge — where machines, sensors, operators, controls systems, production data, and cloud software meet. These are not generic applications for generic business functions. They are custom-built solutions for real production constraints: increasing throughput, improving uptime, reducing scrap, strengthening traceability, accelerating launches, and giving manufacturing leaders better real-time visibility into performance. We are seeking a Forward Deployed Engineer to sit at the intersection of software engineering, manufacturing operations, industrial data, cybersecurity, and business impact. This is a hands-on individual contributor role for an engineer who can embed with plant teams, understand how automated manufacturing systems actually run, and then design, build, integrate, and deploy the software that helps those systems perform better in a highly secured manufacturing technology environment. You'll work across the full stack: application development, cloud infrastructure on GCP, manufacturing data pipelines, IIoT and edge architectures, MQTT-based messaging, OPC-UA connectivity, integrations with MES and automation systems, secure network and data flows, and analytics that turn equipment and production data into operational action. This role is built for engineers who are comfortable on the factory floor and in the codebase. You will not be handed a fully specified spec; you will work with manufacturing, controls, maintenance, quality, process engineering, product, and operations teams to define the problem, validate the data, understand the constraints, and then build and deploy the answer. We are building Ford Energy's manufacturing engineering capability to be software-defined and AI-native from day one: using connected assets, industrial protocols, real-time data, analytics, automation, and applied AI/ML to improve how facilities launch, run, learn, and scale. This is an onsite role reporting to the Software Engineering Manager.