Technical Anchor, Software Engineering

As a Technical Anchor, you will oversee the technical design, development, and delivery of business-critical applications and high-throughput data platforms.

You will establish engineering excellence across full-stack systems, architect resilient Java-based microservices, deliver responsive front-end data exploration interfaces using React or Angular, and design enterprise-grade cloud data streaming and analytical pipelines on GCP.

You will lead distributed engineering squads across local and global locations, driving cloud modernization, data governance, and operational reliability to fuel Ford’s digital transformation.

Responsibilities

1. Technical Leadership, Architecture & Modernization

• Act as the primary technical anchor, translating complex business requirements from legacy applications into scalable, fault-tolerant system designs, architectural blueprints, and execution roadmaps.
• Drive the evolution of Service-Oriented Architecture (SOA), cloud-native microservices, and event-driven patterns.
• Establish coding standards, API contracts (OpenAPI/Swagger), and architectural governance across squads.
• Lead legacy modernization initiatives by re-architecting monolithic services into modular, containerized workloads on GCP.
• Champion agile engineering best practices, enforce test-driven development (TDD), lead comprehensive code reviews, and mentor engineers across full-stack, data engineering, and cloud domains.

2. Full-Stack & Microservices Engineering

• Architect and develop robust, high-performance microservices and RESTful APIs using Java 17+, Spring Boot, Spring Cloud.
• Build responsive, user-centric interfaces using Angular, React, and Node.js that integrate seamlessly with backend APIs.
• Design and standardize API gateway topologies using Apigee.
• Profile and optimize distributed systems end-to-end, including JVM tuning, connection pooling, caching strategies, and database query tuning.

3. Cloud Data Engineering & Analytics

• Architect, build, and maintain real-time streaming and high-volume batch data pipelines leveraging GCP Dataflow (Apache Beam), Dataproc (Spark/Hadoop), and Cloud Pub/Sub.
• Standardize, model, partition, and optimize enterprise datasets within Google BigQuery.

4. Security, Governance & Compliance

• Enforce least-privileged access control across applications, integrating Multi-Factor Authentication (MFA), ADFS, OAuth2/OIDC.
• Implement robust cloud security frameworks, including Role-Based Access Control (RBAC), data encryption (in transit and at rest).
• Partner with cybersecurity, compliance, and governance teams to maintain adherence to enterprise data privacy mandates and corporate security standards.

5. DevOps, Cloud Infrastructure & Observability

• Automate and manage repeatable cloud infrastructure and platform provisioning using Terraform.
• Design and optimize enterprise CI/CD pipelines using GitHub Actions, Tekton.
• Establish proactive monitoring, tracing, and alerting frameworks across Google Kubernetes Engine (GKE), Cloud Run, and Cloud Functions.
• Apply foundational AI and Machine Learning (ML) concepts to accelerate engineering workflows and enhance software capabilities.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical discipline.
• 10+ years of progressive software engineering experience delivering enterprise-scale solutions across full-stack development, distributed computing, and data platforms.

Core Technical Competencies:

• Deep expertise in Java (Java 17+), Spring Ecosystem (Spring Boot, Spring Cloud, Spring Data, Spring Security).
• Hands-on experience developing data visualization and exploration interfaces using React, Angular, or Node.js.
• Proven track record architecting and deploying systems on Google Cloud Platform (GCP), specifically BigQuery, Cloud Run, GKE, and Cloud Pub/Sub.
• Strong practical expertise with relational databases (PostgreSQL, MySQL), NoSQL datastores.
• Hands-on mastery of Infrastructure as Code using Terraform, containerization (Docker, Kubernetes), and automated CI/CD tools (GitHub Actions, Tekton, Maven/Gradle).