Site Reliability Engineer (AI Observability)

Appnovation; Austin (TX); On-site; USD 130,000 - 180,000; Full time

Job summary

Appnovation in Austin, TX is seeking a Site Reliability Engineer to design and implement the observability platform for LLM-based applications. You will own incidents, runbooks, and the onboarding path for internal teams relying on a robust platform.

Role requires hands-on Kubernetes on AWS (EKS), ClickHouse/Redis/PostgreSQL ops, and building monitoring and SLAs from scratch. Consulting experience and calm, process-driven problem solving are valued.

Qualifications

• Hands-on experience with Kubernetes on AWS (EKS)
• Experience with ClickHouse, PostgreSQL and Redis in production
• Experience building monitoring, alerting and service levels from scratch
• Strong incident management and runbook/documentation skills
• Consulting experience and ability to work with client teams

Responsibilities

• Diagnose and resolve platform failures across ClickHouse, PostgreSQL, Redis, and the Kubernetes layer
• Build and maintain monitoring, alerting, and SLAs from scratch
• Own backups, restores, and disaster recovery runbooks
• Plan safe upgrades with rollback strategies
• Triage onboarding and support paths for internal teams

Job description

• Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities
• We’re looking for a Site Reliability Engineer to keep a shared observability platform for LLM-based applications running for a global life sciences client. The platform is built on Langfuse and self-hosted on Kubernetes on AWS, with ClickHouse as the analytical store, PostgreSQL for metadata and Redis as the ingestion queue, all delivered through Argo CD
• Two things need building rather than maintaining. The platform has no monitoring, alerting or defined service levels today, and you will own putting them in place. Infrastructure is defined as code throughout, in Kubernetes manifests, Helm values and Argo CD applications
• Alongside the platform itself, you will own the runbooks that make an incident survivable by someone other than the author, and the onboarding and support path for the internal teams that depend on the platform
• Platform Operations: Diagnose and resolve failures across ClickHouse, PostgreSQL, Redis, the ingestion workers and the Kubernetes layer beneath them, including ingest backpressure from queue depth and worker drain behaviour
• ClickHouse Operations: Own ClickHouse under the operator model, including Keeper quorum, replication, shard and replica topology, and S3 storage tiering
• Provable Backup and Restore: Rehearse the restore, time it, document it and test it against its failure modes, rather than assuming a successful backup job means a recoverable system
• Safe Upgrades: Plan and rehearse upgrades in a lower environment, with a rollback plan that works even if a migration is only partly complete
• Monitoring and Service Levels: Build monitoring, alerting and service levels from scratch, so problems are found here before a user reports them
• Infrastructure as Code: Maintain Kubernetes manifests, Helm values and Argo CD applications so every change goes through the delivery pipeline
• Runbooks and SOPs: Write and maintain runbooks and SOPs that let a colleague resolve an incident without the author present
• Onboarding and Support: Run the onboarding and support path for internal teams that depend on the platform, and triage what they bring
• Automation: Turn recurring operational work into automation
• Upgrade Partnership: Work with the platform engineer who owns what the platform offers. They decide what to adopt and how it is configured; you own the migration and its rollback

• PostgreSQL and Redis operations deep enough to debug metadata-store and queue problems, including backpressure and worker drain
• Hands‑on experience running ClickHouse in production, including replication and Keeper quorum, shard and replica topology, and backup and restore, ideally run through an operator
• Hands‑on experience with Kubernetes on AWS (managed EKS), with routine work done through Helm values and Argo CD applications
• Experience building monitoring and alerting from scratch, including service levels that reflect what users actually experience rather than what is easy to measure
• Strong operational writing: runbooks, SOPs and post‑incident reviews that a colleague can follow unaided during an incident
• Experience upgrading self‑hosted software safely, including schema migrations, rehearsal in a lower environment and a rollback plan for a partly completed migration
• You don’t trust a backup until you’ve restored from it
• You automate anything you have to do twice
• Prior experience and connections in the Life Sciences industry is preferred
• You stay calm in incidents and focus on fixing the process afterward
• You have prior experience in consulting
• You write runbooks for the person on call at 3am, not for yourself
• You work well inside a client team and build trust quickly
• You want to find problems before users do
• Observability engineering, including OpenTelemetry Collector pipelines, alerting design and Grafana dashboards
• OIDC or enterprise SSO integration with a corporate identity provider
• GitHub Actions for plan and apply pipelines with approval gates
• Experience running LLM observability tools such as Langfuse, LangSmith or Arize Phoenix
• Experience in pharma, life sciences or another regulated industry