Ford Motor Company is looking to become a data-first, AI-enabled organization by designing, developing, and optimizing complex industrial solutions that support manufacturing, supply chain, quality, and product development initiatives.
Requirements
- Proficiency in programming languages such as Python and Java.
- Experience with cloud architecture, preferably GCP, including microservices, REST APIs, and serverless platforms like Cloud Run and Cloud Functions.
- Knowledge of DevSecOps tools such as GitHub Actions, Terraform, SonarQube, and GCP Cloud Build or Tekton.
- Strong understanding of scalable, high-performance software solutions, security, and reliability engineering.
- Experience designing modular, decoupled architectures aligned with enterprise standards.
Responsibilities
- Lead the design, development, and deployment of critical platform features and complex applications within the Industrial System Analytics (ISA) platform.
- Write high-quality, production-grade code, perform system integration, and contribute to codebases to support team objectives.
- Drive performance tuning, reliability engineering, capacity planning, and operational excellence across applications.
- Lead experimentation and prototyping efforts for emerging technologies, including AI/ML and large language models (LLMs).
- Translate non-functional requirements such as security, scalability, and reliability into effective technical solutions.
- Design and develop core ISA platform components, ensuring seamless integration with enterprise data platforms and source systems.
- Leverage GCP-native services to enhance security, automation, and operational efficiency.
Other
- 8+ years of experience in software engineering or data platform development.
- Minimum of 5 years of experience mentoring engineers and leading cross-team initiatives.
- Ability to translate complex technical concepts into clear, actionable plans.
- Mentor engineers through code reviews, design sessions, and technical guidance to foster a high-performance engineering culture.
- Collaborate closely with cross-functional teams, including architects, data scientists, product managers, and security teams, to align technical solutions with organizational goals.
