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 team. In 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.

You'll 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.

Full Stack Engineering

• 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

AI/ML Engineering

• 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

Observability & Telemetry

• 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

Quality & DevOps

• 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

Data Engineering (Supporting)

• 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

Required

• Bachelor's 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

Preferred

• 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)