| Location: Dearborn, MI (Hybrid) Industry: Automotive Pay Range: 55/HR-58/HR Years of Experience: 3 Years Minimum Job Description:
We are looking for an experienced and highly motivated Software Engineer to work as part of our high performing engineering team in an exciting and fast paced environment. In this role you will have the opportunity to work with cutting edge cloud-native technologies including Google Cloud Platform (GCP), Spring Boot, Cloud SQL, Dataflow, BigQuery and our platforms. Primary Skills required: React, Typescript, Java, Spring Boot Framework, SQL Experience (Postgres, MSSQL etc.) , application delivery using iterative, test driven, Agile development practices including pairing/mobbing, instrumentation, monitoring and visualization tools including Grafana, Splunk, GCP Cloud Logging | | Skills Required: | | Java, Spring Boot, Acceptance Testing, Integration, GCP, GCP Cloud Run, Google Cloud Platform, Tekton, Spring Security, Python, Big Query, Extract Transform Load (Etl) Java, Spring Boot • Expectation & Example: Build scalable Java 17+ / Spring Boot microservices. E.g., Developing a database-connected REST API from scratch with JUnit tests. Acceptance Testing • Expectation & Example: Write automated end-to-end tests. E.g., validate user checkout flows against business requirements. Integration, GCP • Expectation & Example: Connect microservices with GCP services. E.g., Integrating Spring Boot with GCP services. GCP Cloud Run • Expectation & Example: Containerize and deploy serverless apps. E.g., Packaging a Spring Boot app via a multi-stage Dockerfile and deploying to Cloud Run with auto-scaling limits. Google Cloud Platform (GCP) • Expectation & Example: Manage core GCP infrastructure, networking, and IAM security. E.g., Configuring least-privilege service accounts for Cloud Storage and Secret Manager. Tekton • Expectation & Example: Build cloud-native CI/CD pipelines. E.g., Writing Tekton YAML configurations (Tasks/Pipelines) to test, build, and deploy apps to Kubernetes/GKE. Spring Security • Expectation & Example: Secure enterprise microservices. E.g., Configuring an OAuth2/JWT Resource Server with role-based access control (RBAC). Python • Expectation & Example: Write clean python code for AI/ML application. BigQuery • Expectation & Example: Design schemas and write highly optimized SQL. E.g., Querying millions of rows using partitioning and clustering to minimize processing costs. Extract Transform Load (ETL) • Expectation & Example: Design robust data pipelines. E.g., Building a GCP Dataflow pipeline to extract raw logs, validate schemas, and read them from BigQuery and load into Postgres. | | Skills Preferred: | | Machine Learning, Artificial Intelligence & Expert Systems Machine Learning • Expectation & Example: Integrate and deploy ML models. E.g., Hosting a regression model on GCP Vertex AI and calling its endpoint from a backend service for real-time predictions. Artificial Intelligence & Expert Systems • Expectation & Example: Implement decision engines or leverage GenAI APIs. E.g., Integrating Google’s Gemini API or similar. | | Experience Required: | | Engineer 2 Exp.: Practitioner: 1 coding language or framework. 4+ years in IT; 3+ years in development 1+ years of experience in Machine Learning Language | | Experience Preferred: | | Backend experience in Java (Spring Boot), Experience in application delivery using iterative, Agile development practices including pairing/mobbing, test driven development (TDD), behavior driven development (BDD), continuous integration/continuous delivery (CI/CD), feature flagging, A/B testing, blue/green deployment, SQL experience (Postgres, MSSQL), Experience with instrumentation, monitoring and visualization tools including Grafana, Splunk, GCP Cloud Logging, | | Education Required: | | Bachelor’s Degree | | Education Preferred: | | Master’s Degree | | | | Additional Information: | | ***HYBRID / 4 days per week in the office as required by customer*** Key Responsibilities • Develop and enhance back-end APIs and services, primarily using Java/Spring Boot • Develop data transformation using GCP Dataflow, BigQuery and GCS • Troubleshoot and debug to optimize performance and stability. • Integrate and work with best-in-class analysis tools to improve code security and quality. • Integrate with third party internal and external libraries and APIs as needed to deliver business functionality. • Instrument, measure and monitor application performance using cloud native toolsets (Grafana, Splunk, GCP native tools and more) • Working as part of an Agile team, support the entire application lifecycle from initial concept through design, development, test, deployment and operational support. • Collaborate and innovate with multiple interfacing product teams. • Advocate for engineering excellence, exceptional usability and outstanding quality. | | | |
