Senior Site Reliability Engineer (SRE) - AI-Native Platform Reliability & Security

interface.ai • United State

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AI Summary

Lead the reliability, security, and operational excellence of interface.ai’s AI-native financial services platform, ensuring 99.99% uptime, defining SLOs, and architecting resilient, secure, and scalable infrastructure for enterprise-grade financial institutions. Own incident response, disaster recovery, GitOps deployments, and AI-native operations while setting security and compliance standards for regulated environments. Hands-on IC role requiring deep production Kubernetes, AWS, and AI fluency.

Key Highlights

Own enterprise-grade reliability (99.99% SLOs) and security for an AI-native financial platform serving 10M+ users across 100+ banks/credit unions

Define SLOs, error budgets, disaster recovery (DR) strategies, and incident management processes with blameless post-mortems and SLA reporting

Architect GitOps deployments, cloud infrastructure-as-code (AWS), and AI-native operations with self-healing and golden-path templates for rapid, secure scaling

Lead security posture for regulated financial services, including SOC 2 Type II compliance, IAM least-privilege, supply-chain security, and AI-specific threat protection

Key Responsibilities

Define and enforce customer-facing SLIs/SLOs with an error-budget program governing release decisions

Design and test disaster recovery strategies (regional failover, RTO/RPO per tier) with real failover testing

Implement GitOps-based deployments with progressive delivery, automated analysis, one-click rollback, and drift detection

Architect AWS cloud foundation, Kubernetes platform, and service mesh with IaC for multi-account scale

Lead end-to-end incident management (paging policies, incident commander rotation, status-page automation, SLA reporting)

Build observability systems (metrics, logging, distributed tracing) with dashboards and burn-rate alerts as code

Establish AI-native operations (runbooks, self-healing, golden-path templates) for a small senior team

Own infrastructure security (IAM least-privilege, secrets management, image signing, SBOM, scanning in CI)

Generate compliance evidence for SOC 2 Type II, NCUA/FFIEC exams, and GLBA (change management, access reviews, DR tests)

Protect AI systems against threats (prompt injection, data exfiltration, tenant isolation, abuse detection)

Set guardrails for AI-assisted engineering workflows and credential boundaries

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Technical Skills Required

Production Kubernetes on AWS Infrastructure-as-Code (multi-account scale) Site Reliability Engineering (SRE) practices

Benefits & Perks

100% paid health, dental, and vision care

401(k) and financial wellness perks

Claude Enterprise and frontier AI tools for every employee

Brand-new 21st-floor SF office with floor-to-ceiling views

Discretionary PTO and paid parental leave

$240K–$320K annual compensation range

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Nice to Have

Real-time voice/telephony systems or latency-critical streaming workloads experience

Operating streaming/data platforms and durable workflow engines at scale

Chaos engineering and resilience testing against live environments

Regulated-industry background (fintech, banking, healthcare) including vendor-risk management

Threat modeling for LLM/agentic applications (e.g., OWASP LLM Top 10)

Cloud cost engineering (compute-fleet optimization, LLM spend attribution)

Job Description

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.

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