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Forward Deployed Engineer – Advanced Manufacturing

Ford Motor


Job Location:

Dearborn, MI - USA

Yearly Salary: USD 115000 - 192900
Posted: 1 October 2026 (Yesterday)
Application Deadline: 29 December 2026
Vacancies: 1 Vacancy

Job Summary

Description

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. Youll 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 Energys 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.



Responsibilities

What youll do...

  • Build the Manufacturing Edge: Design develop and deploy software systems that connect automated equipment sensors PLC-adjacent data MES workflows quality systems warehouse systems and cloud platforms. Build the custom edge capabilities that make highly automated facilities observable reliable and continuously improving.
  • Own Industrial Data Flows: Work with and design IIoT architectures MQTT messaging primarily OPC-UA connectivity edge gateways time-series data event-driven systems and manufacturing data models to move trustworthy data from equipment and processes into applications analytics and decision-making workflows.
  • Embed on the Floor and Solve: Work directly with manufacturing operations controls maintenance quality process engineering product and business stakeholders to understand production problems firsthand then translate those needs into shipped software that works in a real facility environment.
  • Deliver Manufacturing Analytics: Build analytics and operational intelligence capabilities for throughput uptime downtime OEE quality scrap traceability cycle time bottlenecks energy usage and launch readiness. Turn raw industrial data into insights alerts dashboards models and workflows that drive measurable operational improvement.
  • Own Delivery End to End: Wear multiple hats across application engineering cloud infrastructure edge deployment integrations automation observability and production support. Success means a deployed capability improving manufacturing outcomes not a handoff between specialized roles.
  • Build Fast Without Breaking the Plant: Move quickly from ambiguity to production-ready systems while respecting manufacturing realities: safety reliability change control cybersecurity secure access network segmentation data protection uptime latency data quality maintainability and the operational consequences of deploying software near physical processes in a highly secured environment.
  • Engineer for Secure Operations: Design and operate solutions for highly secured manufacturing environments where identity access control secrets management network boundaries auditability vulnerability management and secure software delivery are core requirements. Build systems that can be trusted in environments where uptime safety intellectual property and production continuity matter.
  • Apply AI Where It Wins: Use generative AI applied ML anomaly detection predictive analytics intelligent automation and AI-assisted development where they create measurable value for manufacturing operations. Every AI use case should have a clear operational purpose cost justification and path to safe adoption.
  • Uphold the Engineering Standard: Contribute high-quality design and code participate in architecture and code reviews define durable integration patterns for industrial systems and help establish the software data security and deployment standards that allow highly automated facilities to scale.


Qualifications

Youll have...

  • Technical Depth: 5 years of experience as a software engineer manufacturing systems engineer industrial software engineer solutions engineer or similar hands-on engineering role. Strong background in building production software integrating systems and operating across application cloud edge and data layers.
  • Manufacturing and Industrial Systems Experience: Demonstrated experience working with manufacturing environments automation systems plant-floor data MES integrations industrial equipment quality systems maintenance workflows or production operations. Familiarity with highly automated facilities controls-adjacent systems and launch/ramp environments is strongly preferred.
  • IIoT and Edge Connectivity: 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 is required.
  • Manufacturing Analytics: Ability to build or support analytics for OEE throughput downtime cycle time bottleneck detection quality scrap traceability energy consumption and asset performance. Experience turning noisy operational data into trusted metrics dashboards alerts and decision-support tools is highly valued.
  • Modern Stack Experience: 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. Experience working in highly secured environments with identity and access management secrets handling vulnerability remediation audit logging network controls and secure deployment practices is strongly preferred. Experience with data platforms streaming architectures and AI/ML-enabled automation is a plus.
  • Bias for Deployed Outcomes: A track record of taking ambiguous high-stakes operational problems from first conversation to working software in production. Comfortable being judged on measurable manufacturing outcomes not just code written or designs produced.
  • Adaptability and Field Readiness: Comfortable working in fast-changing manufacturing environments spending time onsite with operators and engineers troubleshooting real systems and balancing speed with safety reliability cybersecurity secure access maintainability and uptime requirements in highly controlled production environments.
  • Communication and Influence: Excellent communication and relationship-building skills with the ability to translate between software engineering controls operations quality maintenance product and business stakeholders as a hands-on individual contributor.
  • High Autonomy High Accountability: Comfortable operating with minimal process and significant latitude owning the consequences of what you ship and building the playbook for software-defined manufacturing as the organization scales.

You may not check every box or your experience may look a little different from what weve outlined but if you think you can bring value to Ford Motor Company we encourage you to apply!

As an established global company we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe or keep you close to home Will your career be a deep dive into what you love or a series of new teams and new skills Will you be a leader a changemaker a technical expert a culture builderor all of the above No matter what you choose we offer a work life that works for you including:

  • Immediate medical dental vision and prescription drug coverage
  • Flexible family care days paid parental leave new parent ramp-up programs subsidized back-up child care and more
  • Family building benefits including adoption and surrogacy expense reimbursement fertility treatments and more
  • Vehicle discount program for employees and family members and management leases
  • Tuition assistance
  • Established and active employee resource groups
  • Paid time off for individual and team community service
  • A generous schedule of paid holidays including the week between Christmas and New Years Day
  • Paid time off and the option to purchase additional vacation time.

This position is a salary grade 8 and ranges from $115000-$192900.

Final determination of salary grade will be based on candidates skills and experience and base salary will be set within the applicable range according to job scope responsibility and competitive market value.

For more information on salary and benefits click here: sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race religion color age sex national origin sexual orientation gender identity disability status or protected veteran the United States if you need a reasonable accommodation for the online application process due to a disability please call 1-.

This position is hybrid with a requirement to be onsite four or more days per week. #LI-Hybrid

Company: As Ford establishes a wholly owned subsidiary focused on Battery Energy Storage Systems this role will initially be employed by Ford and is expected to transition to the subsidiary within one year.

#LI-KF2

#FordEnergy




Required Experience:

IC


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