Methods and Software Engineer

The Ford Racing Motorsports Performance Engineering Group is seeking a Methods & Software Engineer to support and development of our Vehicle Dynamics, Aerodynamics and Performance Engineering tool set.  This role will be responsible for developing and adapting tools that fit into an enterprise architecture strategy that aligns with business objectives, data mesh principles, and distributed cloud-native systems.

In this position...

The Methods & Software Engineer will deliver projects and features to support simulation, prototype testing, wind tunnel testing, CFD and total vehicle performance.  In this position, you will collaborate directly and continuously with technical engineering groups and software development partners to deliver enterprise level solutions across a wide array of programs.  The team is focused on building software to realize efficiencies across multiple platforms, leveraging existing software base and Google Cloud Platform, (GCP), functionality.  

This is a hybrid role and requires at least 4 days per week in the Concord, NC (preferred) or Allen Park, MI office.

What you’ll do…

Tool Development

• Develop and consolidate tools to integrate with next generation simulation architecture.
• Design software to increase efficiency of technical teams with a fully integrated approach.
• Focus on modern application design with a modular framework for integration with multidisciplinary systems.

Enterprise & Cloud Architecture

• Support the technical vision and strategy for cloud modernization, leveraging Google Cloud Platform (GCP).
• Design, implement and integrate scalable, resilient, and secure cloud-native architectures, integrating machine learning, big data, and observability solutions.
• Establish best practices for automation, CI/CD, and DevSecOps to drive operational efficiency and software quality.
• Support technical governance to ensure alignment with business objectives, security policies, and compliance requirements.

Data & AI Enablement

• Assist Principal Architect and implement event-driven data architectures that support data mesh principles, data as a product, and domain-driven design (DDD).
• Collaborate with Principal Architect and software groups to define strategies for data interoperability, governance, and self-service platforms to enable AI and analytics-driven decision-making.
• Contribute to the adoption of MLOps practices, ensuring seamless deployment and monitoring of machine learning models in production.

Technology & Collaboration

• Collaborate with engineering teams to define scalable and cost-efficient architectural solutions.
• Work with engineers and developers, fostering a culture of continuous learning and technical excellence.
• Drive technical innovation by researching emerging technologies and working cross functionally with technical groups to bring new technology forward. 

You'll have...

• Bachelor's degree in Computer Science, Engineering, or other relevant technical discipline (Master's degree preferred).
• 5+ years of experience in software architecture, cloud engineering, or enterprise systems design, preferably in a motorsports setting, and the experience includes a combination of the following skills: C#, Python, Go, TypeScript, MATLAB, Java.

Even better, you may have…

• Knowledge in cloud-native platforms (GCP, AWS, Azure) and containerized microservices architectures (Kubernetes, Docker, Istio, Service Mesh).
• Strong knowledge of distributed data systems, event-driven architectures (Kafka, PubSub, etc.), and API design (GraphQL, REST, gRPC) .
• Hands-on experience with Infrastructure as Code (Terraform, Ansible), CI/CD pipelines, and observability tools (Prometheus, OpenTelemetry, Grafana).
• Excellent communication skills.
• Strong ability and desire to work collaboratively with multiple groups and personnel across numerous disciplines. 
• Excellent problem-solving and analytical skills.
• Experience in Motorsports.
• Experience with SQL, PostgreSQL (preferred).
• Experience in data governance, security, and compliance in cloud environments.
• Hands-on experience with AI/ML deployment, MLOps, and model monitoring.
• Certifications such as GCP Professional Cloud Architect, AWS Solutions Architect, or Azure Solutions Architect.
• Previous experience standing up, developing and/or managing enterprise level software solutions.
• Experience with Github.
• Experience with Linux and containerizing.
• Experience with Python, AngularJS,