# AI-Accelerated Full Stack Software Development Engineer **Company**: Ford **Location**: Dearborn **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Salary**: Competitive salary and benefits package **Category**: Engineering **Industry**: Automotive **Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/64118?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_2f7d830c-25a ## Description We're seeking an experienced Full Stack Software Development Engineer to join our Vehicle Software and Systems Engineering (VSSE) team. As a key member of our team, you will design, build, and maintain secure and scalable web applications using Angular and cloud-native services on Google Cloud Platform (GCP). You will apply AI-assisted development practices to improve productivity, code quality, test coverage, documentation, and delivery speed while helping transform early-stage AI prototypes into secure, production-ready enterprise applications. Responsibilities: - Design, develop, test, and maintain full stack web applications using Angular, modern backend services, APIs, and cloud-native technologies on GCP. - Build responsive, intuitive, and performant user interfaces that simplify complex engineering workflows. - Develop backend services, RESTful APIs, data integrations, and reusable components to support AI-enabled applications. - Integrate applications with enterprise data sources, authentication systems, engineering tools, and AI services. - Ensure applications are secure, scalable, reliable, observable, and maintainable in production environments. - Participate in architecture reviews, technical design discussions, code reviews, and production readiness assessments. - Use AI coding assistants and generative AI tools to accelerate software development, refactoring, debugging, documentation, and code reviews. - Apply AI to support requirements analysis, user story refinement, acceptance criteria generation, design exploration, and technical documentation. - Leverage AI to generate and improve unit tests, integration tests, end-to-end tests, regression tests, and test data. - Use AI-assisted approaches for defect triage, log analysis, root-cause investigation, and production support. - Identify opportunities to automate repetitive SDLC activities and improve developer productivity. - Promote responsible and secure use of AI tools while protecting Ford data, intellectual property, and enterprise standards. - Build, deploy, and support applications using Google Cloud Platform services and cloud-native architecture patterns. - Work with GCP services such as Cloud Run, Cloud Functions, App Engine, GKE, Cloud Storage, Pub/Sub, Firestore, BigQuery, Cloud SQL, Secret Manager, Cloud Build, Artifact Registry, and Cloud Monitoring, as applicable. - Support CI/CD pipelines, automated testing, containerization, infrastructure automation, and environment management. - Collaborate with DevSecOps and platform teams to improve deployment reliability, scalability, performance, and observability. - Apply cloud security best practices, including identity and access management, secrets management, network controls, and data protection. - Help build and enhance AI-enabled applications that support Ford Product Development teams across electrical, software, and vehicle systems domains. - Integrate applications with LLMs, AI APIs, retrieval systems, vector databases, enterprise knowledge sources, and workflow automation tools. - Contribute to reusable AI platform capabilities such as prompt templates, AI service wrappers, evaluation workflows, telemetry, and feedback loops. - Support low-code or self-service AI capabilities that allow technical and non-technical users to create guided workflows or AI-assisted solutions. - Explore and apply emerging AI development patterns, including retrieval-augmented generation, agentic workflows, Model Context Protocol, and Agent-to-Agent integration where appropriate. - Work closely with product owners, designers, data scientists, software engineers, DevOps engineers, and business stakeholders. - Translate user needs and product requirements into high-quality technical solutions. - Contribute to backlog refinement, sprint planning, estimation, demos, retrospectives, and delivery planning. - Use metrics, telemetry, and user feedback to improve application performance, usability, adoption, and business impact. - Share knowledge with the team on AI-assisted engineering practices, reusable development patterns, and full stack best practices. Qualifications: - Bachelor’s Degree in Computer Science, Software Engineering, Engineering, Information Systems, or a related technical field. - 7+ years of professional software development experience. - 7+ years of experience building modern web applications using Angular, TypeScript, HTML, CSS/SCSS, and modern frontend engineering practices. - Experience developing backend services, APIs, and integrations using one or more languages or frameworks such as Node.js, Java, Python, Spring Boot, NestJS, Express, or similar. - Hands-on experience with Google Cloud Platform or equivalent cloud platform. - Practical experience using AI coding assistants, generative AI tools, or LLM-based development workflows to accelerate software delivery. - Understanding of how AI can support the SDLC, including requirements analysis, coding, testing, documentation, debugging, deployment, and operational support. - Experience with REST APIs, authentication/authorization patterns, secure coding practices, and enterprise application integration. - Experience with Git, CI/CD pipelines, automated testing, code reviews, and Agile software development practices. - Ability to write clean, maintainable, well-tested code and troubleshoot complex full stack issues. - Strong communication and collaboration skills with the ability to work across technical and non-technical teams. ## Skills ### Required - Angular - Google Cloud Platform - Cloud Run - Cloud Functions - App Engine - GKE - Cloud Storage - Pub/Sub - Firestore - BigQuery - Cloud SQL - Secret Manager - Cloud Build - Artifact Registry - Cloud Monitoring - CI/CD pipelines - automated testing - containerization - infrastructure automation - environment management - cloud security best practices - identity and access management - secrets management - network controls - data protection - LLMs - AI APIs - retrieval systems - vector databases - enterprise knowledge sources - workflow automation tools - prompt templates - AI service wrappers - evaluation workflows - telemetry - feedback loops - low-code or self-service AI capabilities - retrieval-augmented generation - agentic workflows - Model Context Protocol - Agent-to-Agent integration --- Source: [Apply at efds.fa.em5.oraclecloud.com](https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/64118?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)