Full Stack Software Engineer-Manufacturing Digital Engineering

We are seeking a highly skilled collaborative and forward-thinking AI/ML Full Stack Engineer to join our product this role you will deliver robust full-stack development leveraging cloud-native microservices on GCP while also driving AI Engineering initiatives designing and integrating GenAI models agentic workflows and ML pipelines to solve complex business challenges.

Youll work closely with a team of engineers who use automated CI/CD pipelines to continuously ship clean secure and production-ready code. A key aspect of this role is building strong observability and telemetry into our systems collecting both operational metrics and business metrics through logging monitoring tracing and alerting to ensure performance reliability and rapid issue detection across our platforms.

The ideal candidate is passionate about software craftsmanship building scalable and high-performance applications and staying current with cutting-edge AI capabilities.

- Design and develop responsive performant web applications using Angular/React TypeScript and modern frontend frameworks

- Build scalable backend services and RESTful APIs using Spring Boot Java and microservices architecture

- Build reusable frameworks and work closely with DevOps to ensure the platform is highly available scalable and fault tolerant

- Migrate existing legacy applications to GCP and modernize codebases to current frameworks (Spring Boot Angular/React)

- Conduct code reviews and ensure adherence to standards design patterns and architecture principles

- Contribute to AI-driven initiatives including integrating GenAI capabilities and agentic workflows within the GCP ecosystem

- Design develop and deploy ML models using Python TensorFlow PyTorch or scikit-learn

- Build end-to-end ML pipelines data preprocessing feature engineering model training evaluation and deployment on Vertex AI

- Collaborate with product managers and stakeholders to translate business problems into AI/ML solutions

- Build strong observability into the platform including automated performance monitoring logging and distributed tracing (e.g. Splunk Dynatrace OpenTelemetry)

- Instrument systems to collect both operational metrics (latency error rates throughput) and business metrics (usage patterns adoption value delivery)

- Ensure high availability quick issue detection and reliable production support through proactive alerting

- Actively participate in Test-Driven Development (TDD) CI/CD and DevOps practices as part of software craftsmanship and Agile XP

- Automate unit integration and performance testing (JUnit Selenium/Playwright) and ensure application security through SAST/DAST practices

- Implement robust CI/CD processes quality gates and maintain high code coverage standards

- Work with data pipelines and cloud-based data storage/processing technologies for handling large datasets

- Leverage GCP data services (BigQuery Dataflow Pub/Sub) for analytical and ML workloads

- Apply data preprocessing cleaning and feature engineering to prepare data for model training

- Bachelors degree in Computer Science Engineering Data Science or a related field (or equivalent experience)

- 5 years of professional software development experience

- Strong proficiency in Java (Spring Boot Spring Cloud Spring Security) and front-end frameworks (Angular or React TypeScript)

- Experience building and deploying cloud-native applications on Google Cloud Platform (Cloud Run App Engine Cloud Functions BigQuery Pub/Sub)

- Hands-on experience with Python for AI/ML development using frameworks such as TensorFlow PyTorch or scikit-learn

- Experience with microservices architecture REST API design and containerization (Docker Kubernetes)

- Proven experience with TDD methodology CI/CD pipelines (GitHub Actions Jenkins Tekton) and code quality tools (SonarQube Checkmarx)

- Experience building observability solutions monitoring logging tracing and alerting for both operational and business metrics

- Proficiency with version control (GitHub) and Infrastructure as Code concepts (Terraform is a plus)

- Strong problem-solving analytical and communication skills

- Experience working in Agile/XP environments

- Experience with Generative AI/LLM applications prompt engineering or agentic AI workflows

- Familiarity with Vertex AI AI Platform or similar managed ML services

- Experience with data pipeline tools (Dataflow DBT Astronomer/Airflow)

- Knowledge of MLOps practices model versioning experiment tracking model serving

- Experience with databases (PostgreSQL BigQuery MongoDB) and data modeling

- Familiarity with Tekton and Terraform for CI/CD and infrastructure provisioning

- GCP Professional certifications (Cloud Engineer ML Engineer or Data Engineer)