We are seeking a Full-Stack Software Engineer to join our team, responsible for validating third-party cloud AI models on our platforms. This role blends front-end development, back-end services, and cloud-native technologies to build end-to-end systems that ensure high-quality AI integrations for our customers.
Youll design and deliver scalable microservices and intuitive web interfaces that help benchmark, validate, and publish AI modelsplaying a key role in how customers experience AI on our enterprise platforms.
What you will do:
Build and maintain full-stack applications that power model validation pipelinesfrom backend microservices to front-end dashboards.
Develop clean, efficient APIs to automate model benchmarking, inference performance testing, and accuracy evaluation.
Design user-friendly web interfaces that visualize model insights and validation results for both internal teams and external users.
Contribute to CI/CD workflows for automated testing, deployment, and continuous integration of model validation tools.
Work closely with platform engineers, DevOps specialists, and data scientists to ensure a seamless AI model lifecycle experience.
Troubleshoot issues across the stack, improve performance, and ensure security and reliability across services.
Actively participate in agile processes, sprint planning, and technical reviews, contributing to a collaborative, high-performing team culture.
Share ideas that improve user experience, developer workflows, and validation system scalability.
Youll design and deliver scalable microservices and intuitive web interfaces that help benchmark, validate, and publish AI modelsplaying a key role in how customers experience AI on our enterprise platforms.
What you will do:
Build and maintain full-stack applications that power model validation pipelinesfrom backend microservices to front-end dashboards.
Develop clean, efficient APIs to automate model benchmarking, inference performance testing, and accuracy evaluation.
Design user-friendly web interfaces that visualize model insights and validation results for both internal teams and external users.
Contribute to CI/CD workflows for automated testing, deployment, and continuous integration of model validation tools.
Work closely with platform engineers, DevOps specialists, and data scientists to ensure a seamless AI model lifecycle experience.
Troubleshoot issues across the stack, improve performance, and ensure security and reliability across services.
Actively participate in agile processes, sprint planning, and technical reviews, contributing to a collaborative, high-performing team culture.
Share ideas that improve user experience, developer workflows, and validation system scalability.
Requirements:
Proficiency in front-end frameworks (e.g., React, Vue, or Angular) and strong skills in HTML, CSS, and modern JavaScript/TypeScript
Experience developing and maintaining backend microservices using Python, Go, Node.js, or similar languages
Solid understanding of REST APIs, web architecture, and database design (SQL or NoSQL)
Familiarity with CI/CD pipelines, GitOps workflows, and automated testing practices
Comfort working across the stack, with an eagerness to contribute wherever needed
Basic understanding of AI/ML workflows and MLOps (not required, but a plus)
Strong debugging, troubleshooting, and communication skills
Bachelors degree in Computer Science or related field, or equivalent practical experience
Nice to have:
Experience with containerization and orchestration tools like Docker and Kubernetes
Knowledge of data visualization libraries (e.g., D3.js, Chart.js, Plotly)
Exposure to AI model inference frameworks or data pipelines
Contributions to open source or a passion for collaborative development.
Proficiency in front-end frameworks (e.g., React, Vue, or Angular) and strong skills in HTML, CSS, and modern JavaScript/TypeScript
Experience developing and maintaining backend microservices using Python, Go, Node.js, or similar languages
Solid understanding of REST APIs, web architecture, and database design (SQL or NoSQL)
Familiarity with CI/CD pipelines, GitOps workflows, and automated testing practices
Comfort working across the stack, with an eagerness to contribute wherever needed
Basic understanding of AI/ML workflows and MLOps (not required, but a plus)
Strong debugging, troubleshooting, and communication skills
Bachelors degree in Computer Science or related field, or equivalent practical experience
Nice to have:
Experience with containerization and orchestration tools like Docker and Kubernetes
Knowledge of data visualization libraries (e.g., D3.js, Chart.js, Plotly)
Exposure to AI model inference frameworks or data pipelines
Contributions to open source or a passion for collaborative development.
This position is open to all candidates.
