Artificial Intelligence Specialist #1058864
Job Description:
Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming
 
Key Responsibilities:

• Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities
• Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence
• Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming
• Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation

 
Skills Required:

• Ability to communicate and work with cross-functional teams and all levels of management , Big Query,, GitHub, API, AI/ML, CI/CD, Scripting

 
Skills Preferred:

• AIPGEE

 
Experience Required:

• Specialist Exp: 5+ experience in relevant field

 
Experience Preferred:

• AI & Developer Platforms: Experience with AI-powered engineering tools such as GitHub Copilot, GitHub Actions, SonarQube, and modern developer platforms, including cloud migrations and technology modernization initiatives.
• CI/CD & Automation: Strong expertise in CI/CD, DevSecOps, and automating software delivery pipelines using GitHub Actions, scripting, and AI-enabled workflows.
• AI-Assisted Development: Leverages AI for code generation, code review, quality analysis, and developer productivity while ensuring secure and maintainable software. Software Engineering: Proficient in Java, Spring Boot, and modern application development practices. Cloud & Platform Technologies: Experience with containers, Kubernetes/CaaS, PCF, Linux, WebSphere, and cloud-native platforms.
• Agile Delivery: Works effectively in Agile teams, contributing to planning, prioritization, and iterative delivery with a software craftsmanship mindset.
• Collaboration & Customer Focus: Partners with product and engineering teams to translate business needs into technical solutions and drive platform adoption.
• Governance & Continuous Improvement: Ensures compliance with security policies and service standards while continuously improving engineering processes through automation and AI.

 
Education Required:

• Bachelor's Degree

 
Education Preferred:

• Master's Degree

 
Additional Information :

• AI Adoption and Ethical Use: Embrace the exploration and application of AI technologies while adhering to ethical guidelines and ensuring responsible implementation.
• CI/CD Pipeline Development and Management: Design, build, and maintain efficient CI/CD pipelines using source code management tools (e.g., GitHub) and build/deployment tools (e.g., Jenkins, GH Actions) with hands-on experience to ensure effective code management and deployment.
• API Interaction and Data Gathering: Understand API collections and demonstrate proficiency in reading and writing JSON responses from various applications to gather metrics.
• Collaboration and Communication: Demonstrate strong collaborative and communication skills to effectively work with others, navigate complex decision-making processes, and adapt to working across different time zones with sensitivity to cultural and geographical differences.
• Technology Research and Implementation: Research and evaluate new technologies, influencing and implementing enterprise technology shifts and trends to improve Ford's application delivery processes.
• Troubleshooting and Support: Leverage strong technical expertise in an application development language to support product teams by troubleshooting build, scan analysis, testing, and deployment issues within the build pipeline.
• GCP Service Management: Demonstrate a strong understanding of various GCP services, including Compute Engine, Cloud SQL for PostgreSQL, and Google Kubernetes Engine (GKE), to effectively manage and utilize these services. DevOps and DevSecOps Practices: Implement and adhere to DevOps and DevSecOps principles to streamline development and enhance security.
• Problem Solving: Apply strong analytical and problem-solving skills to resolve technical challenges.
• Continuous Learning: Demonstrate the ability to learn new technologies and processes such as Azure, Extreme Programming, Agile practices, etc.,