Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness.
Provide technical leadership and mentorship, influence engineering standards and architecture decisions, and deliver measurable improvements in reliability, MTTR, operational toil, engineering productivity, and infrastructure efficiency.
What We Need To See
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience, with 10+ years of software engineering, SRE, infrastructure, or distributed-systems experience and demonstrated technical leadership.
Strong software engineering expertise in Go, Python, or equivalent languages, with experience designing and building production-grade distributed systems, platform services, APIs, and automation.
Proven experience owning complex software/platform initiatives across multiple teams or infrastructure domains, from architecture and implementation through adoption and measurable impact.
Deep understanding of distributed systems, event-driven architectures, microservices, APIs, and high-throughput data processing, including technologies such as Kafka, NATS, gRPC, or equivalent.
Strong experience with modern observability and telemetry platforms, including OpenTelemetry, Prometheus, VictoriaMetrics, Vector, Loki, Grafana, ClickHouse, or equivalent technologies.
Strong SRE and infrastructure knowledge across Kubernetes/OpenShift, VMware, bare-metal, storage, networking, and/or cloud environments, with experience using Terraform, Ansible, or equivalent automation technologies.
Demonstrated ability to solve ambiguous problems, influence technical direction without direct authority, mentor engineers, establish engineering standards, and deliver measurable operational and business outcomes.
Ways To Stand Out From The Crowd
Experience building software and reliability platforms for large-scale on-premises infrastructure, particularly Storage, Compute, Networking, VMware, and Kubernetes/OpenShift.
Deep understanding of storage and infrastructure telemetry, including IOPS, latency, NVMe health, SAN/NAS topology, block/object storage, and infrastructure failure domains.
Experience building self-healing systems, automated remediation, predictive operations, or autonomous SRE capabilities.
Production experience applying Generative AI, AIOps, LLMs, or Agentic AI to incident triage, RCA, operational intelligence, debugging, or remediation; experience with LangChain, LlamaIndex, AutoGen, or equivalent is a plus.
Experience building high-performance platform services using FastAPI, gRPC, or equivalent technologies.
