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About This Role
Overview
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At Ford, you’ll work on ideas that matter, alongside passionate people who want to make a global impact. Together, we’re shaping the next era of transportation—grounded in purpose, driven by progress. Make your move.
- Job Type: Full time
- Work Type: Remote
We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.
Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.
Ford Motor Company is seeking a Senior AI \& Full Stack Engineer within our Corporate Communications team to shape the next generation of intelligent content experiences. In this role, you will have full\-stack responsibility for our online publication application, From the Road (FTR), built on Adobe Experience Manager (AEM).
You will bridge the gap between web experiences and advanced AI—integrating Generative AI (GenAI), AI\-powered search, and Generative Engine Optimization (GEO) capabilities directly into the FTR platform. To establish a deep understanding of our application architecture, you will also actively contribute to core, day\-to\-day full\-stack web development. You will partner closely with cloud architects, AEM platform engineers, and product designers to deliver scalable, AI\-first content architectures.
1\. AI, GenAI \& GEO Engineering
- Build enterprise taxonomies, entity models, and knowledge graphs integrated with AEM to convert static pages into structured, reusable content.
- Develop dynamic schema\-generation systems (JSON\-LD, Schema.org) to automate content tagging and maximize search engine crawling.
- Design backend AI pipelines using LLMs and RAG to automatically generate article summaries, key facts, and FAQs from editorial content.
- Implement automated testing and evaluation frameworks to measure LLM retrieval accuracy, answer quality, and grounding before production release.
- Execute Generative Engine Optimization (GEO) and technical SEO strategies to optimize content visibility across conversational AI platforms and search engines.
2\. Full\-Stack \& API Development
- Develop robust, scalable backend services and REST/GraphQL APIs using Java or Python.
- Build and maintain high\-performance, secure microservices and integration layers supporting AI\-powered experiences.
- Develop frontend features and components using React, successfully bridging data from modern AI middleware to the web experience.
3\. Enterprise Platform Integration (AEM Ecosystem)
- Partner with enterprise AEM engineering teams to integrate AI capabilities into content repositories, enabling automated metadata enrichment, AI search retrieval, and authoring workflows.
4\. DevOps \& Cloud Engineering
- Develop and maintain CI/CD pipelines using enterprise\-standard tools (e.g., GitHub Actions, Jenkins).
- Implement Infrastructure as Code (Terraform) to deploy scalable AI platforms powered by Google Cloud technologies.
- Support observability, monitoring, operational readiness, and DevSecOps compliance for all deployed AI services.
5\. Core Application Development \& Agile Execution
- Standard Feature Development: Leverage AEM and React to build scalable features and resolve technical issues, ensuring the day\-to\-day stability and evolution of the From the Road application.
- Domain Familiarization: Actively contribute to standard application features and bug fixes to build deep, hands\-on domain knowledge of the platform's codebase and editorial workflows.
- Cross\-Functional Collaboration: Partner closely with business stakeholders, UX/UI designers, and product managers to translate requirements into robust, user\-focused, and scalable solutions.
- Agile Integration: Actively participate in all agile ceremonies including daily stand\-ups, sprint planning, retrospectives, and backlog refinement to design, develop, and deliver feature implementations within sprint commitments.
Minimum Qualifications:
- 10\+ years of professional software engineering experience in full\-stack or backend development.
- Production AI Experience: Hands\-on experience building and deploying production\-grade AI/ML applications, particularly with Large Language Models (LLMs) and Retrieval\-Augmented Generation (RAG) architectures.
- Strong Programming Foundations: High proficiency in Java (the native backend language of our CMS) and/or Python.
- Modern Frontend Experience: Strong, hands\-on experience building web interfaces and components using React.
- Enterprise API Design: Demonstrated experience designing, building, and integrating high\-performance, secure APIs (REST and GraphQL) to seamlessly bridge decoupled enterprise services.
- DevOps \& CI/CD: Practical experience with modern DevOps practices, CI/CD pipelines (e.g., GitHub Actions, Jenkins), and cloud\-native architecture.
- Strong Systems Thinker: Excellent system design, problem\-solving, and cross\-functional technical leadership skills.
Preferred Qualifications
- Familiarity with Adobe Experience Manager (AEM) or other enterprise Content Management Systems (CMS).
- Experience with semantic search, knowledge graphs, or content intelligence systems.
- Hands\-on experience with prompt engineering and LLM evaluation frameworks.
- Familiarity with Google Cloud Platform (GCP) or similar enterprise cloud ecosystems.
- Exposure to enterprise digital communications or managing large\-scale content platforms
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:
- Immediate medical, dental, vision and prescription drug coverage
- Flexible family care days, paid parental leave, new parent ramp\-up programs, subsidized back\-up childcare and more
- Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
- Vehicle discount program for employees and family members and management leases
- Tuition assistance
- Established and active employee resource groups
- Paid time off for individual and team community service
- A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
- Paid time off and the option to purchase additional vacation time.
This position is a salary grade 7 and ranges from $99,600\-$166,600\.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/GSR
Visa sponsorship is not available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1\-888\-336\-0660\.
\#LI\-Remote
\#LI\-PW1
Salary Context
This $99K-$166K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Ford Motor Company, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($133K) sits 39% below the category median. Disclosed range: $99K to $166K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Ford Motor Company AI Hiring
Ford Motor Company has 7 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Data Scientist, AI Software Engineer. Positions span Dearborn, MI, US, Remote, US. Compensation range: $166K - $218K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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