Forward Deployed Engineer Advanced Manufacturing, Ford Energy

Ford • Dearborn, MI

4d • $115,000 - $192,900 • Hybrid

About The Position

Ford Energy is seeking a hands-on individual contributor to build and deploy software at the intersection of software engineering, manufacturing operations, industrial data, cybersecurity, and business impact. The role focuses on custom manufacturing-edge solutions that connect equipment, sensors, operators, controls systems, production data, and cloud software to improve throughput, uptime, scrap, traceability, manufacturing launches, and real-time operational visibility.

The engineer will embed with plant teams and work across application development, GCP cloud infrastructure, manufacturing data pipelines, IIoT and edge architectures, MQTT messaging, OPC-UA connectivity, MES and automation integrations, secure network and data flows, and operational analytics. The role requires working directly with manufacturing and business stakeholders to understand and validate problems and data, account for facility constraints, and deliver production-ready software. Ford Energy aims to build software-defined, AI-native manufacturing capabilities using connected assets, industrial protocols, real-time data, analytics, automation, and applied AI/ML.

This is an onsite role reporting to the Software Engineering Manager. The posting also states that the position is hybrid, with a requirement to be onsite four or more days per week. The role will initially be employed by Ford and is expected to transition to Ford Energy’s wholly owned battery energy storage systems subsidiary within one year.

Requirements

• At least 5 years of experience as a software engineer, manufacturing systems engineer, industrial software engineer, solutions engineer, or in a similar hands-on engineering role.
• Strong background building production software, integrating systems, and working across application, cloud, edge, and data layers.
• Demonstrated experience with manufacturing environments, automation systems, plant-floor data, MES integrations, industrial equipment, quality systems, maintenance workflows, or production operations.
• Hands-on familiarity with IIoT architectures, MQTT, OPC-UA, edge gateways, industrial protocols, event-driven architectures, time-series data, sensor-data ingestion, and secure connectivity between plant-floor systems and cloud platforms.
• Ability to build or support manufacturing analytics for OEE, throughput, downtime, cycle time, bottlenecks, quality, scrap, traceability, energy consumption, and asset performance.
• Experience turning noisy operational data into trusted metrics, dashboards, alerts, and decision-support tools.
• Experience with Go, Python, TypeScript, API design, OpenShift, GCP or comparable cloud platforms, containerized services, infrastructure-as-code, CI/CD, observability, and secure production operations.
• Track record of taking ambiguous, high-stakes operational problems from initial discussion to working software in production.
• Comfort working in changing manufacturing environments, spending time onsite with operators and engineers, and troubleshooting real systems.
• Excellent communication and relationship-building skills, including the ability to translate between software engineering, controls, operations, quality, maintenance, product, and business stakeholders.
• Comfort operating with minimal process and significant latitude, taking accountability for shipped work, and building practices for software-defined manufacturing.
• Legally authorized to work in the United States; employment eligibility will be verified at hire.

Nice To Haves

• Experience with highly automated facilities, controls-adjacent systems, and manufacturing launch or ramp environments.
• Experience working in highly secured environments with identity and access management, secrets handling, vulnerability remediation, audit logging, network controls, and secure deployment practices.
• Experience with data platforms, streaming architectures, and AI/ML-enabled automation.

Responsibilities

• Design, develop, and deploy software connecting automated equipment, sensors, PLC-adjacent data, MES workflows, quality systems, warehouse systems, and cloud platforms.
• Build custom edge capabilities that improve observability, reliability, and continuous improvement in highly automated facilities.
• Design and operate IIoT architectures, MQTT messaging, OPC-UA connectivity, edge gateways, time-series data flows, event-driven systems, and manufacturing data models.
• Move trustworthy equipment and process data into applications, analytics, and decision-making workflows.
• Work with manufacturing operations, controls, maintenance, quality, process engineering, product, and business stakeholders to understand production problems and deliver software that works in a facility.
• Build analytics and operational intelligence for throughput, uptime, downtime, OEE, quality, scrap, traceability, cycle time, bottlenecks, energy usage, and launch readiness.
• Deliver insights, alerts, dashboards, models, and workflows that support measurable operational improvement.
• Own delivery across application engineering, cloud infrastructure, edge deployment, integrations, automation, observability, and production support.
• Build production-ready systems while respecting safety, reliability, change control, cybersecurity, secure access, network segmentation, data protection, uptime, latency, data quality, and maintainability requirements.
• Design and operate secure manufacturing solutions with identity and access control, secrets management, network boundaries, auditability, vulnerability management, and secure software delivery.
• Apply generative AI, applied machine learning, anomaly detection, predictive analytics, intelligent automation, and AI-assisted development when they provide measurable manufacturing value and can be adopted safely.
• Contribute high-quality designs and code, participate in architecture and code reviews, define durable industrial integration patterns, and help establish software, data, security, and deployment standards.
• Troubleshoot real systems onsite and balance speed with safety, reliability, cybersecurity, maintainability, and uptime.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Flexible family care days, paid parental leave, new parent ramp-up programs, and subsidized backup childcare.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• Vehicle discount program for employees and family members, and management leases.
• Tuition assistance.
• Employee resource groups.
• Paid time off for individual and team community service.
• Paid holidays, including the week between Christmas and New Year’s Day.
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed