5 years of experience as a software engineer with a focus on backend systems and platform engineering including at least 2 years in DevOps and 2 years in development.
Deep experience with all computing environments (GCP AWS Onprem or Azure).
Strong understanding of containerization and orchestration (Docker Kubernetes).
Experience with observability tools (Prometheus Grafana ELK/EFK etc.).
Experience working on ML platforms or supporting ML workloads in production.
Familiarity with data infrastructure (e.g. Kafka Spark Airflow).
Proficiency in languages like Go Python or Java; experience with infrastructure-as-code (Terraform Pulumi etc.).
Experience with providing technical support of custom-developed systems to customers.
Responsibilities:
Proficiency in AI-assisted coding; able to do multiple tasks at once and manage AI agents to quickly execute.
Drive infrastructure automation CI/CD and monitoring/alerting pipelines.
Collaborate with Field Engineering teams to support PoCs and Platform deployments in customer Cloud VPCs and on-prem.
Deploy scale and optimize ML/NLP workloads especially model inference.
Lead initiatives to improve system reliability scalability and developer experience.
Contribute to architecture and infrastructure decisions as we scale our platform.
Champion best practices in code quality testing and DevOps culture across the team.
Design implement and maintain scalable and secure backend services and platform components.
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