Senior Software Engineer - Data Infrastructure

Join a data infrastructure team responsible for the foundational systems powering large-scale cloud storage and backup services. In this senior engineering role, you will design and build automation, observability, and system health capabilities that improve reliability, durability, and performance across a fleet of thousands of servers. You will help engineers provision, configure, and repair infrastructure independently while developing tools that identify issues before they become incidents. Working across services and teams, you will lead technical design discussions, deliver complex projects from conception through rollout, and turn operational challenges into scalable engineering solutions. This remote opportunity is ideal for an experienced backend engineer who enjoys solving ambiguous systems problems, improving infrastructure at scale, and making a lasting impact on platform reliability.

• Design and develop automation frameworks that enable engineers to provision, configure, and repair fleet infrastructure independently.

• Extend and improve observability systems across metrics, logs, traces, and alerts to monitor platform health and identify degradation.

• Build reporting tools, dashboards, and visualizations that provide clear insights into fleet health, capacity, and operational trends.

• Develop system health tooling to detect hardware failures, configuration drift, and capacity risks before they lead to incidents.

• Lead technical design discussions and create clear design documentation for changes spanning multiple services and engineering teams.

• Drive large-scale feature implementation from initial design through deployment, including migrations, data backfills, and rollout planning.

• Collaborate with on-call engineers to identify recurring operational work and incident patterns, converting findings into automation and improved monitoring.

• Identify opportunities to improve system throughput, reliability, and operational efficiency across the infrastructure platform.

• At least 7 years of backend development experience in an enterprise environment using an object-oriented or systems programming language such as Java, Rust, C++, C#, or Go.

• Proven experience designing automation frameworks or platforms that other engineers rely on.

• Experience building and operating large-scale software systems distributed across thousands of servers.

• A track record of developing internal platform services, operational tooling, or deployment and configuration pipelines used by engineering teams.

• Working knowledge of observability technologies such as Prometheus, Grafana, OpenTelemetry, ELK, Datadog, or equivalent, including service instrumentation and actionable alert design.

• Strong Linux fundamentals and experience working in bare-metal or hybrid infrastructure environments rather than relying exclusively on fully managed cloud services.

• Professional experience incorporating AI-assisted development tools such as Gemini, Cursor, Claude Code, or similar into engineering workflows.

• Familiarity with the full software development lifecycle, including architecture and design, implementation, testing, deployment, and rollout.

• Strong analytical and problem-solving abilities, with the curiosity to understand complex problems before proposing solutions.

• Clear, proactive communication skills in a remote working environment, including keeping teammates informed, identifying blockers early, and maintaining progress.

• A collaborative, adaptable mindset, strong attention to detail, commitment to engineering best practices, and willingness to contribute in a fast-paced company environment.

• Excellent troubleshooting, interpersonal, and written and verbal communication skills.

• Proficiency in Java.

• Familiarity with configuration management or infrastructure-as-code tools such as Ansible, Salt, Puppet, Chef, or Terraform.

• Experience defining service-level objectives (SLOs), managing error budgets, and reducing alert noise in large-scale environments.

• Knowledge of time-series databases and query languages such as PromQL.

• Experience automating hardware lifecycle processes, including burn-in testing, failure detection, drive replacement, and decommissioning.

• Experience identifying and implementing CPU and I/O performance improvements.

• Understanding of Linux internals and file systems.

• Familiarity with hard drive performance optimization, including host-managed shingled magnetic recording (SMR).

• Experience developing and interpreting operational models, dashboards, and reports.