Senior Fullstack Engineer

We are looking for a Full Stack Developer to join the AI Hub engineering team in Bengaluru. You will work across the stack to build scalable, high-quality features that empower ML practitioners to develop, manage, and monitor AI applications on eBay's platform. This is a high-impact role with direct access to platform users across the company. Your work will directly build how researchers and engineers experience the AI Platform every day.
Responsibilities:
Own the end-to-end delivery of full-stack features on the AI Hub portal, building responsive TypeScript/React UIs and Node.js backend services that surface the ML lifecycle to platform users.
Design, build, and maintain Java-based REST APIs, and actively contribute to core AI Platform services including the Experiment Management System (EMS), Model Management System (MMS), and AI Metadata Service.
Build and maintain production observability dashboards using Prometheus and Grafana, giving ML practitioners real-time visibility into their workloads, experiments, and model deployments.
Design and operate CI/CD pipelines using Argo CD and GitOps-based tooling to streamline platform deployments and improve release reliability.
Collaborate directly with ML researchers, Applied Scientists, and infrastructure engineers to identify developer pain points and translate them into platform improvements that accelerate AI development velocity.
Drive engineering throughput by embedding AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) into daily workflows, setting the standard for how the team writes, reviews, and ships code.
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field, with 5+ years of software engineering experience building production systems.
Strong proficiency in TypeScript and React for building performant, developer-facing web applications; comfortable owning the full frontend stack.
3+ years of backend development experience with strong proficiency in Java for building scalable REST APIs; working knowledge of Node.js or Python is a plus.
Solid foundation in data structures, algorithms, system design, and distributed systems fundamentals.
Hands-on experience with observability and CI/CD tooling such as Prometheus, Grafana, Argo CD, or equivalent GitOps-based pipelines.
Demonstrated use of AI-assisted development tools (e. g., Claude Code, Cursor, GitHub Copilot, Windsurf) to improve coding efficiency and output quality.
Nice to Have:
Experience with MLOps platforms such as MLflow, Weights & Biases, or equivalent experiment and model lifecycle tooling.
Familiarity with Kubernetes and containerised environments (Docker, Helm).
Prior experience building developer-facing internal platforms, portals, or SDKs.
Exposure to the machine learning lifecycle including model training, experiment tracking, inference serving, or LLM deployment.

Experience
9-13 yrs