Software Engineer

Ford-Motor-Company; San Bartolo Naucalpan Centro; Híbrido; MXN 600.000 - 1.000.000; Jornada completa

Descripción de la vacante

Ford Motor Company is seeking an experienced software engineer to design, develop, and maintain scalable enterprise applications and cloud services aligned with FSC customer experiences. You will build AI-powered solutions using conversational and Generative AI approaches, and advance RAG implementations leveraging enterprise knowledge sources.

The role requires collaboration across product, UX, data, security, and platform teams to drive engineering excellence, automated testing, and DevSecOps

Formación

• Bachelor's degree in Computer Science, Engineering, or related technical discipline.

Responsabilidades

• 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.

Conocimientos

Java

Spring Boot

REST APIs

Cloud-native

CI/CD

DevSecOps

Team collaboration

Analytical thinking

Educación

Bachelor's degree in Computer Science, Engineering, or related technical discipline

Herramientas

GCP

Cloud Run

API Gateway

Pub/Sub

Kubernetes

Descripción del empleo

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.