Software Engineer

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.