# Staff Platform & Reliability Engineer at interface.ai > Onsite · United States · Staff · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Ainterface-ai%3Ab623f8f8-5e7c-4f30-a24e-0bb88219e5d9 (read 2026-11-06). ## Facts (observed) - Company: [interface.ai](https://alderhq.app/companies/interface-ai) - Location text: San Francisco - Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco") - Posted: 2026-09-18 (49 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/interface-ai/b623f8f8-5e7c-4f30-a24e-0bb88219e5d9 - Skills listed (inferred): AWS, Kubernetes ## Pay and sponsorship - Posted pay: $240k–$320k per year (from the listing's pay field) - Market band for similar posted roles (SF Bay Area, n 911): p25 $205k, median $240k, p75 $284k ## Description (the employer's text) ### About interface.ai interface.ai is the agentic AI platform for financial services — bringing conversational and agentic AI to the credit unions and community banks that serve everyday Americans. We're not a lab, we're not a demo company, and we're not burning runway on hypotheticals. We are in production, generating real revenue, and on a mission that matters: making intelligent financial services available to the millions of people who've never had a private banker. More than 100 banks and credit unions run on interface.ai, reaching over 10 million people. Many products are live today; the biggest bets — an AI-first contact center and an AI-native consumer banking experience — are what comes next. Backed by $30M in Series A funding and already cash-flow positive, we're at the inflection point: a proven product, paying customers, and a profitable business rebuilding itself as an AI-native company to lead a world where agents, not software, do the work. ### The Role You own how the platform ships and how it stays up — the reliability and security backbone behind every conversation on interface.ai. Our customers are banks and credit unions, and the bar for trust is high: real money, real regulators, and the uptime our customers count on. This role holds the platform to the enterprise-grade, 99.99% reliability we're known for and sets the engineering practices that keep it there as we scale. You'll define the SLOs, own the deploy path, run incidents when they happen, and build the platform so a small, senior team working with AI tooling can operate it with confidence — and you'll set the reliability and security bar the rest of the org builds against. This is a hands-on, senior-most IC seat. What we mean by senior isn't tenure — it's judgment: you've run production systems people depend on, you think in failure modes and containment, and AI tooling is already part of how you work every day. ### What You'll Own Reliability & SLOs — define customer-facing SLIs and SLOs across product surfaces, run an error-budget program that governs release decisions, and hold the platform to its reliability bar. Resilience & disaster recovery — own the DR strategy: regional failover, written RTO/RPO per tier, resilience against third-party dependency failure, and recovery you've actually tested rather than just planned. Deploy & delivery — a GitOps deploy path with progressive delivery, automated analysis, and one-click rollback for every service, plus drift detection and a full change audit trail. Cloud & infrastructure-as-code — the AWS foundation, fully managed as code; the Kubernetes platform and service mesh; capacity, cost, and scale. Incident management — end to end: paging and severity policy, an incident-commander rotation, status-page automation, blameless post-mortems with tracked actions, and SLA reporting to customers. Observability — metrics, logging, and distributed tracing across services; dashboards and alerts as code; burn-rate alerting that pages on what actually matters. AI-native operations — build the automation and guardrails that let a small, senior team operate the platform with AI in the loop: runbooks encoded for safe automation, self-healing for routine work, and golden-path templates that ship new services with SLOs, alerts, secrets, and policy built in. ### Security & Compliance You own the infrastructure's security posture — including the parts unique to running an AI platform in regulated financial services. Cloud & cluster security — IAM least-privilege across accounts, secrets management with a single source of truth, admission control and network policy on every cluster, image signing / SBOM / scanning in CI, and cloud-audit and threat-detection feeds as first-class alert sources. Compliance evidence — own the infrastructure evidence for SOC 2 Type II and for customer and regulator reviews (NCUA/FFIEC examinations, GLBA): change management, access reviews, backup/restore, and DR test records, automated wherever possible. Securing AI systems — protect the platform against AI-specific threats such as prompt injection, data exfiltration through tools, tenant isolation for retrieval stores, and abuse detection on public-facing endpoints — and set the guardrails and credential boundaries for AI-assisted engineering workflows. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Ainterface-ai%3Ab623f8f8-5e7c-4f30-a24e-0bb88219e5d9 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.