Sr Java Full Stack Developer

About The Role

We are seeking a highly skilled Senior DevOps Engineer to join our product team within the DaVinci Data Engine domain. This role is ideal for an engineer with deep experience in distributed systems operations, Kubernetes cluster management, networking, high-availability architectures, and cloud platforms such as AWS and Azure.

(You will support our AI and LLM delivery platform, which drives our internal and customer used AI services to enhance internal processes, as well as customer facing product solutions.)

You will be responsible for building, operating, and evolving the CI/CD, deployment, and runtime platforms that support our products. This includes pipeline automation, security scanning and artifact verification, service monitoring and reliability, and overall platform quality.

Your work will also include enabling and operating LLM models (both local and cloud-hosted), supporting deployment, validation, and debugging of LLM prompts, and ensuring that prompt templates can be safely promoted through automated pipelines for use in agentic AI service architectures.

Key Responsibilities

• Design, build, and operate reliable, scalable, and secure platform infrastructure to support product teams.
• Own and evolve CI/CD pipelines, including build automation, artifact promotion, security scanning, and release workflows.
• Operate and create Harness deployment pipelines, be able to debug and analyze problems in runtime of Harness pipelines
• Operate and maintain Kubernetes-based distributed clusters, ensuring high availability, scalability, and resilience.
• Manage container images, registries, and artifact repositories, including access controls, verification, and lifecycle policies.
• Enable and support LLM runtime environments, including deployment, configuration, validation, and operational debugging.
• Implement and maintain monitoring, logging, alerting, and health checks to ensure service reliability and fast incident response.
• Debug and resolve complex production issues across cloud and on‑premises environments.