Job Description
Beyond delivering customer-facing solutions, the FSC team is actively investing in reusable AI platform capabilities, evaluation frameworks, agent-based architectures, and engineering excellence practices that can be leveraged across Ford Credit.
This role offers the opportunity to work on cutting-edge technologies, collaborate with global teams, and influence the future direction of AI-enabled customer experiences.
- Design, develop, and maintain scalable enterprise applications, APIs, and cloud services supporting FSC customer experiences.
- Build AI-powered digital solutions using conversational, generative AI, and agent-based architectures.
- Design and implement Retrieval Augmented Generation (RAG) solutions that leverage enterprise knowledge sources.
- Develop AI Agents and Multi-Agent systems capable of automating complex workflows and customer interactions.
- Contribute to the design and evolution of GenAI evaluation frameworks, including automated assessment and quality measurement capabilities.
- Collaborate closely with Product Management, UX, Data, Architecture, Security, and Platform Engineering teams.
- Drive engineering excellence through modern software development practices, automated testing, observability, and DevSecOps.
- Participate in solution design, technical reviews, production support, and continuous improvement initiatives.
- Help establish reusable platform capabilities that can scale across multiple products and business domains.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related technical discipline.
- Significant experience developing enterprise web applications and distributed systems.
- Strong proficiency in Java and Spring Boot.
- Experience designing and implementing REST APIs and microservices.
- Experience working in cloud-native environments.
- Strong understanding of software architecture, system design, and engineering best practices.
- Experience with automated testing, CI/CD, and DevSecOps practices.
- Strong analytical, problem-solving, and communication skills.
- Ability to effectively collaborate within a globally distributed team.
Preferred Technical Experience
Application Development
- Java 17+
- Spring Boot
- Microservices Architecture
- REST APIs
- React
- TypeScript
- Event-Driven Architectures
- API Integration Patterns
Cloud & Platform Engineering
- Google Cloud Platform (GCP)
- Cloud Run
- API Gateway
- Pub/Sub
- Cloud Storage
- Cloud-native deployment and operational practices
- Infrastructure Automation
Artificial Intelligence & Conversational Experiences
- Conversational AI platforms
- Virtual Assistant solutions
- AI Agents and Agentic Workflows
- Multi-Agent Architectures
- Prompt Engineering
- Context Engineering
- Enterprise Chatbots
- Responsible AI and AI Governance
Large Language Models (LLMs)
- Building applications leveraging foundation models and Generative AI technologies
- LLM orchestration and integration
- Structured response generation
- Tool-calling patterns
- Function orchestration
- AI application lifecycle management
Retrieval-Augmented Generation (RAG)
- Semantic Search
- Embedding Models
- Vector Databases
- Enterprise Knowledge Retrieval
- Knowledge Grounding
- Context Management
- Retrieval Optimization
- Document Ingestion Pipelines
AI Evaluation & Quality Frameworks
- GenAI Evaluation Frameworks
- LLM-as-a-Judge Methodologies
- Automated AI Assessments
- AI Quality Metrics
- Benchmarking and Scoring Approaches
- Experimentation and A/B Testing
- Evaluation Automation Pipelines
- Continuous Quality Monitoring
Google Cloud AI Services
Experience with one or more of the following:
- Vertex AI
- Gemini Models
- Vertex AI Agent Builder
- Vertex AI Search & Conversation
- Vertex AI Vector Search
- Model Deployment and Serving
- Machine Learning Services
- Generative AI Platform Capabilities
What Success Looks Like
The successful candidate will help:
- Deliver innovative AI-powered customer financing experiences.
- Advance conversational and agent-based solutions within FSC.
- Build scalable RAG and GenAI capabilities leveraging enterprise knowledge.
- Establish evaluation frameworks that improve the quality, safety, and effectiveness of AI solutions.
- Strengthen engineering excellence through automation, testing, cloud-native practices, and operational maturity.
- Contribute to strategic AI platform capabilities that can be reused across Ford Credit.
