Senior Site Reliability Engineer

Job Description

About the opportunity

AI Engineering builds the shared agent platform behind Xplor's AI capabilities: the agent runtime, model gateway, retrieval, guardrails, evaluations, and cost controls. We build the hard parts once, so every product team can ship AI features faster and safely.

We're looking for a hands-on Site Reliability Engineer to own how our agent platform behaves in production. AI workloads bring new reliability problems: long streaming responses, background agents, model-provider quotas, outputs that can fail silently, agents that take real actions, and spend that grow with usage. You'll treat them as first-class engineering problems. As AI agents take on more of our operational work, you'll decide what they're allowed to do and make sure they do it safely.

Why this role is exciting

• Reliability for a new kind of workload. The playbook for running AI agents in production is still being written, and you'll help write it.
• Scale with real stakes. A multi-tenant platform serving thousands of businesses, and AI features they depend on to run their day.
• Greenfield foundations. Define the SLOs, alerting, game days, agent guardrails, and standard deployment paths that every product team will build on.
• Cost is an engineering problem. Token economics, model routing and cost per task matter as much as uptime.
• AI-native operations. Use AI agents to automate toil, speed up investigations and improve infrastructure code; with the approval gates, scoped permissions and audit trails that make it safe.

What you'll do

• Define SLOs and error budgets for agent APIs, streaming and background work, including quality signals like task success, tool-call failures and evaluation regressions, and alert on what matters to customers.
• Own the platform's AWS infrastructure (ECS on Fargate, Aurora PostgreSQL, Redis and Amazon Bedrock) as Terraform delivered through Spacelift.
• Build observability in Datadog and Coralogix with OpenTelemetry, including AI signals like token usage, provider latency and cost per task.
• Make data stores resilient, with tested backups and restores, failover, defined disaster recovery targets (RTO/RPO) and safe migrations.
• Build resilience into the model layer: provider failover, quota and rate-limit management, and safe rollout and rollback of model and prompt changes.
• Protect the platform under multi-tenant load with per-tenant quotas, isolation and circuit breakers that stop runaway agents and runaway spend.
• Partner with Security on operational controls for AI risks, including prompt injection, excessive agent permissions and unbounded consumption (OWASP Top 10 for LLM Applications).
• Set the guardrails for AI agents that work on our infrastructure: what they can change, which actions need human approval, and how every action is audited.
• Work with Security and Privacy to keep model inference and customer data in the right regions for customers in Australia, New Zealand, the US, the UK and the EU.
• Lead incident response and blameless reviews, take part in on-call, and run game days for the failures that matter most.
• Make deployments safe by default, and give product teams simple, standard ways to run agent workloads.
• Track and reduce cloud and model spend.

Our stack

• Cloud: AWS: ECS on Fargate, Aurora PostgreSQL with pgvector, ElastiCache Redis, CloudFront, Route 53, Secrets Manager and SSM
• AI: Amazon Bedrock and other model providers behind a multi-provider gateway
• Infrastructure as code: Terraform, delivered through Spacelift
• Observability: Datadog, Coralogix and OpenTelemetry
• Delivery: GitHub Actions, containers, Amazon ECR and preview environments

This position has an annual base salary range of $150,000 to $180,000 USD.

This is a fully remote role open to candidates based anywhere in the U.S., excluding Hawaii and Alaska. We'd prefer candidates in the Eastern or Central time zones.

#LI-Remote

Qualifications

What would make me a good candidate?

• 7+ years in SRE, DevOps or platform engineering, running multi-tenant SaaS in production
• Strong AWS experience and Terraform at scale (Spacelift, Terraform Cloud, Atlantis or similar)
• Experience building SLO-based alerting and observability with Datadog or similar tools, ideally with OpenTelemetry
• A track record of leading incidents calmly and turning post-incident reviews into lasting fixes
• Hands-on PostgreSQL operations: backups, point-in-time recovery, performance tuning and upgrades
• Production-quality coding skills for automation and tooling
• A least-privilege mindset and a disciplined approach to using AI tools

It would be great if you also have

• Experience running LLM or AI workloads in production, or a real interest in learning how they fail differently from traditional services
• Use of AI agents to automate operational work, such as incident triage, runbooks or infrastructure-code review, and a clear sense of where human review still matters
• Experience in regulated environments such as SOC 2 or PCI DSS
• Amazon Bedrock quotas and inference profiles, policy as code, LLM evaluation, AI security tooling, or multi-region data-residency requirements

At Xplor, we believe that the best innovation and ideas happen at the intersection of differences - people of different cultures, generations, disciplines, and lived experiences. So even if you think you don't quite tick all the boxes, we still encourage you to apply.

Additional Information

Some of our perks and benefits are:

• Paid Parental Leave benefit programs
• #GiveBackDays/Commitment to social impact - 3 extra days off to volunteer and give back to your local community
• Ongoing dedication to Diversity & Inclusion initiatives such as D&I Council, Global Mentorship Program
• Access to free mental health support
• Flexible working arrangements

Ready to apply?

To start your application, please submit your resume, and we will be in touch as soon as we can. Please include the word "moonshot" at the top of your message to the Hiring Manager so that we know you took the time to read our job ad.

Before you apply

To be considered for employment, you must be legally authorized to work in the country where the role is advertised. This applies to remote roles too. Xplor does not sponsor visas, either at the time of hire or at any later time. We're also not able to offer contractor arrangements or Employer of Record engagements for this position at this stage.

Please apply through our careers portal or external job boards only. We're unable to upload emailed applications, as our process requires you to answer screening questions directly.

We also invite you to check out our Candidate FAQs for more information about our recruitment process xplor.com/recruitment-faqs/.

Interview Recording and Background Checks

As part of our hiring process, successful candidates will be asked to complete background and identity verification checks. Many of our roles are remote, and to protect both candidates and our business from recruitment fraud, we may record video interviews during the process. We keep any recordings and related data only for as long as the hiring process is active and do not retain them afterwards.

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