Forward Deployed Engineer, Ford Energy

In this position...

While we leverage industry-standard platforms for our core ERP, CRM, and MES capabilities, our hardest and high-value problems live at the edge — where customers, operations, physical assets, and data meet software. These are not generic applications for generic business functions. They are custom-built solutions to real operational problems for real customers, built where buying a platform doesn't make sense and where we can move faster and smarter by building ourselves, accelerated by AI.

We are seeking Forward Deployed Engineers to sit at the intersection of engineering and business impact. This is a hands-on individual contributor role for engineers who want to own outcomes, not tickets. Engineers will be directly embedded with internal stakeholders and external customers to understand real operational problems, then designing, building and deploying the software that solves them. You'll work across the full stack: application development, cloud infrastructure on GCP, enterprise data platform for AI scale, integrations with manufacturing and warehousing technology, and automation and tooling that take an idea to a production deploying.

This role is built for engineers who thrive in ambiguity, want direct exposure to the business and customer problems they're solving, and want outsized ownership and accountability over what they ship. You will not be handed a fully specified spec, instead you will be in the room helping define the problem, and then you'll build and deploy the answer.

We are building Ford Energy's engineering organization to be AI-native from day one, not an organization that bolts AI onto existing process, but one where intelligent automation, orchestration and applied AI/ML are simply how work gets done.

This is an onsite role reporting to the Software Engineering Manager.

• - Technical Depth: 5+ years of experience as a software engineer with a strong background in hands-on development, systems architecture, and integrating production systems. Comfortable wearing multiple hats (application engineering, cloud infrastructure, and production delivery automation) rather than specializing in only one layer. Experience spanning both greenfield development and enterprise platform integrations is highly valued.
• - Bias for Deployed Outcomes: A track record of taking ambiguous, high-stakes problems from first conversation to working software in production and comfortable being judged on outcomes delivered, not just code written. Prior forward-deployed, field engineering, solutions engineering, or startup founding-engineer experience is a strong plus.
• - AI & Velocity Mindset:
  Demonstrated experience with AI/ML in production or applied business contexts, combined with a strong practice of using generative AI tools to accelerate development velocity across the SDLC. Focused on building smart, automated systems that solve business problems, not just traditional static software.
• - Modern Stack
  
  Experience:
  
  Experience with Go, Python, Type Script, API design, GCP, and modern cloud architectures. Experience with infrastructure-as-code, cloud environments, and delivery automation is expected. Experience with MQTT, IoT, edge computing, manufacturing technologies, and enterprise platform integrations (ERP, CRM, MES) is highly valued. Familiarity with AI engineering frameworks and intelligent automation patterns is a plus.
• - Adaptability:
  Ability to navigate ambiguous, fast-changing environments and deliver simple, secure solutions under tight timelines.
• - Communication:
  Excellent communication and relationship-building skills, with the ability to partner effectively across diverse technical and business teams as an individual contributor.
• - High Autonomy, High…