Jobs / Xplor Technologies
Senior Site Reliability Engineer
Xplor Technologies · Myrtle Point, OR, United States
Myrtle Point, OR, United StatesExp: 7+ yrs150,000-200,000 USD/yearlyRemote
Remuneration
150,000-200,000 USD/yearly
Location
Myrtle Point, OR, United States
Visa sponsorship
No visa sponsorship
Xplor does not sponsor visas, either at the time of hire or at any later time.
Job summary
Own the production reliability and safe operation of a shared, multi-tenant AI agent platform, addressing challenges such as streaming responses, background workloads, model-provider quotas, agent safety, and usage-driven costs. Define service-level objectives and operational guardrails, manage AWS infrastructure and resilient data stores, build observability and model-provider failover, and lead incident response. The platform uses technologies including Terraform, Spacelift, Datadog, OpenTelemetry, Amazon Bedrock, and PostgreSQL.
Benefits
Paid parental leaveThree additional volunteer daysMental health supportFlexible working arrangementsDiversity and inclusion initiativesGlobal mentorship program
Qualifications
- At least 7 years of SRE, DevOps, or platform engineering experience operating multi-tenant SaaS in production.
- Strong AWS experience and experience managing Terraform at scale.
- Experience building SLO-based alerting and observability with Datadog or similar tools; OpenTelemetry experience is preferred.
- Experience leading incidents and turning post-incident reviews into lasting improvements.
- Hands-on PostgreSQL operations, including backups, point-in-time recovery, performance tuning, and upgrades.
- Production-quality coding skills for automation and tooling.
- A least-privilege mindset and disciplined use of AI tools.
Responsibilities
- Define SLOs, error budgets, and customer-focused alerts for agent APIs, streaming, and background workloads.
- Own AWS infrastructure provisioned with Terraform through Spacelift.
- Build observability using Datadog, Coralogix, and OpenTelemetry, including token usage, provider latency, and cost per task.
- Ensure data-store resilience through tested backups and restores, failover, disaster recovery targets, and safe migrations.
- Implement model-provider failover, quota and rate-limit management, and safe model and prompt rollouts and rollbacks.
- Protect multi-tenant workloads with per-tenant quotas, isolation, and circuit breakers.
- Define permissions, approval requirements, and audit controls for AI agents operating on infrastructure.
- Lead incident response and blameless reviews, participate in on-call, and run game days.
- Provide standard deployment paths for agent workloads and reduce cloud and model spend.
- Partner with Security and Privacy on AI risk controls and regional data residency.
Skills
AWSCloudFrontDatadogECSFargateGitHubGitHub ActionsMakeOpenTelemetryPostgreSQLRedisRoute 53Secrets ManagerTerraformTerraform CloudC#DockerGoJavaNode.jsOpen Policy AgentPythonRubySnykTypeScriptVault
Industry
AI engineeringMulti-tenant SaaS
Relocation
No