Software Gigs

Design and own cloud infrastructure foundations, core platform services, and observability systems that enable reliable deployment across customer environments (on-premise, cloud, or hybrid). Build production-grade Kubernetes infrastructure, internal APIs, deployment pipelines, and monitoring/alerting layers using infrastructure-as-code. Instrument service-level objectives and health signals to ensure measurable reliability and reproducible, secure deployments across all environments.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams. The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.

Own and evolve infrastructure, deployment systems, and cloud environments powering Clinically AI's healthcare AI platform. Design and maintain GCP infrastructure with focus on GKE, Kubernetes, and secure multi-environment deployments; build Infrastructure-as-Code using Terraform and Helm charts; optimize CI/CD pipelines with GitHub Actions; implement observability, security best practices, and incident response. Work closely with Backend, AI, and Product teams to support scalable infrastructure for services, AI pipelines, and high-throughput workloads.

Own and evolve the cloud infrastructure, deployment systems, and CI/CD pipelines powering Clinically AI's healthcare platform on GCP. Design and maintain cloud infrastructure using GKE, Terraform, and Helm; build reliable CI/CD pipelines with GitHub Actions; implement observability, security best practices, and incident response processes. Work closely with Backend, AI, and Product teams to support scalable infrastructure for AI pipelines, real-time processing, and multi-environment deployments. Operate with significant autonomy across cloud-native architecture while optimizing for performance, reliability, cost, and compliance.

Staff Site Reliability Engineer at SHEIN responsible for operating and evolving large-scale, mission-critical production systems with 24/7/365 on-call participation. Design, build, and maintain observability solutions (metrics, logs, traces, alerting) with AI-powered anomaly detection; own and operate core open-source infrastructure (APISIX, Nginx, Kubernetes, Kafka, Elasticsearch, Redis, Consul, Etcd, Zookeeper). Automate operational workflows, reduce incident frequency and MTTR, and provide technical leadership across global engineering teams. Requires strong software engineering skills, deep Linux/networking/distributed systems expertise, and passion for solving problems at scale.

This Staff Platform Engineer role owns operational strategy and technical direction for enterprise GitLab (3,000+ users) and JFrog Artifactory platforms, leading cloud-native transformation and Kubernetes migrations. The position requires 7+ years of enterprise-scale platform operations, 5+ years each with self-managed GitLab and Artifactory in high-availability deployments, and 3+ years of deep Kubernetes expertise. Responsibilities include designing multi-region active-active systems, establishing cloud-native best practices, mentoring team members, and influencing organizational standards for platform engineering and developer experience. Required expertise spans Linux kernel/networking, PostgreSQL high availability, AWS/Azure/GCP, Kubernetes operators, service mesh (Istio), infrastructure-as-code (Terraform), observability (Prometheus), and production automation in Python, Go, and Bash.