Required Skills: NATS, JetStream, VMware, bare-metal Kubernetes environments

Job Description

Senior Software Engineer (L5) – Platform & Release Engineering

We are seeking a Senior Software Engineer to build and scale the platform, infrastructure, and release systems that enable TernStack deployments across SaaS, cloud, and on-premises environments. You will work across Go, Kubernetes, Terraform, and CI/CD to deliver reliable, cloud-agnostic deployments and operational excellence.

Key Responsibilities

• Design and maintain Terraform-based Infrastructure as Code for consistent, automated deployments across cloud and on-prem environments.
• Develop platform services, sidecars, admission webhooks, and Kubernetes controllers in Go.
• Build and manage core infrastructure components, including NATS/JetStream, S3-based audit storage, and platform services.
• Create and optimize CI/CD pipelines with automated testing, ephemeral environments, and performance validation.
• Implement Kubernetes-native solutions for CRD management, drift detection, policy enforcement, and operational automation.
• Support architecture for AI gateway deployments in customer VPCs, SaaS control planes, and future multi-region expansion.
• Drive a culture of testing, reliability, and continuous improvement across the platform.

Required Qualifications

• 7+ years of software engineering experience, with significant exposure to platform, infrastructure, or cloud-native engineering.
• Strong proficiency in Go and experience building distributed systems and platform services.
• Deep expertise in Terraform and Infrastructure as Code practices.
• Hands-on experience designing and operating Kubernetes platforms, including controllers, operators, CRDs, and admission webhooks.
• Strong understanding of CI/CD systems, automated testing frameworks, and release engineering best practices.
• Experience working across cloud and on-premises environments.
• Familiarity with distributed messaging systems, networking, and platform security concepts.

Preferred Qualifications

• Experience with multi-cloud architectures and SaaS platform operations.
• Knowledge of NATS, JetStream, VMware, and bare-metal Kubernetes environments.
• Experience building AI/ML platform infrastructure or supporting large-scale inference workloads (e.g., vLLM).
• Strong understanding of observability, reliability engineering, and performance optimization.