Staff DevOps Engineer — Real-Time AI Infra & Scale

AlleyCorp; San Jose (CA); On-site; USD 190,000 - 237,000; Full time

Job summary

Archer, an aerospace company in San Jose, seeks a Staff DevOps Engineer to architect and scale core services and real‑time data pipelines for AI products. You’ll bridge AI models to production, ensuring low latency, reliability, and security in a high‑throughput streaming environment.

You will own the full lifecycle, collaborate across AI Research, Eng, and Data Science, and mentor teammates in distributed systems and automated operations. Attractive base pay and equity potential.

Qualifications

• BS/MS/PhD in CS, software engineering, or related field.
• 5+ years in backend systems, distributed architectures and infra.
• Proficiency in Java, Python and/or Rust for high‑performance backend.
• Production experience with stream processing (Apache Flink).
• Observability stacks like Grafana/Prometheus/ELK.
• Containerization and orchestration (Docker, Kubernetes) with auto‑scaling.
• Cloud platforms (AWS, GCP, Azure) and IaC tools (Terraform/OpenTofu, Ansible).
• GitOps and CI/CD automation (Argo CD).
• Relational DBs (PostgreSQL) and in‑memory stores (Redis).

Responsibilities

• Architect and maintain backend systems and data pipelines.
• Build scalable cloud infrastructure for real‑time AI apps.
• Containerize, deploy, orchestrate, and monitor ML models and infra.
• Own end‑to‑end lifecycle from design to capacity planning.
• Improve performance, observability, and reliability; manage incidents.
• Mentor team members; promote DevOps culture and best practices.

Skills

Backend systems

Distributed architectures

Cloud platforms

IaC tooling

Kubernetes

Terraform/OpenTofu

CI/CD pipelines

Java/Python/Rust

Observability

PostgreSQL/Redis

Education

BS/MS/PhD in CS or related

Tools

Docker

Kubernetes

Argo CD

Terraform

Job description

Archer, an aerospace company in San Jose, seeks a Staff DevOps Engineer to architect and scale core services and real‑time data pipelines for AI products. You’ll bridge AI models to production, ensuring low latency, reliability, and security in a high‑throughput streaming environment.

You will own the full lifecycle, collaborate across AI Research, Eng, and Data Science, and mentor teammates in distributed systems and automated operations. Attractive base pay and equity potential.