Senior SRE

The Role

We're building the financial data platform at Accelerant — the premium, claims, and paid data products that underpin financial processing, reserving analysis, and the monthly close — and it needs to stay fast, resilient, and observable as we scale. You'll drive the reliability and observability strategy across the platform and the enterprise systems it depends on: Velocity, MuleSoft, D365, Snowflake, Fabric, and the streaming and integration layers that move data through it. You are a key decider about what gets measured, how we define reliability, and where engineering needs to invest to keep production healthy.

What You'll Do

• Drive the reliability and observability initiative
• Own the reliability roadmap end to end
• Prove a repeatable define → emit → ingest → dashboard → alert metric pipeline, set SLOs and error budgets, prioritize the work, and drive execution
• Partner with engineering on what we monitor, how, and when — indexing on user impact over low-level infrastructure
• Harden the foundational platform
• Take the financial data platform from functional to enterprise-grade, with a focus on availability, performance, and recoverability
• Expand observability breadth and depth
• Implement a scalable incident and review process
• Route alerts Datadog → Incident.io with ServiceNow as the system of record, and set severity standards, escalation norms, and follow-up tracking that actually closes the loop
• Build the tooling that automates routine operations, self-heals common failures, and surfaces signal over noise
• Establish data lineage and retention, and validate reliability at scale — 5,000+ transactions before go-live — through auto-remediation, capacity planning, and actionable dashboards
• Build specialized SRE agents using Cursor AI
• Use Cursor as your build environment
• Treat the agents as products solving specific problems
• Host SRE agents on the AI fabric
• Partner with the AI platform team to deploy your agents on the org's AI fabric

What You'll Bring

• Proven experience designing, operating, and scaling reliable production systems
• Deep hands-on expertise with modern observability tooling — Datadog, Prometheus/Grafana, and OpenTelemetry — including both push and pull ingestion patterns
• Strong background defining SLIs, SLOs, and error budgets — and translating them into business-level KPIs, not just infrastructure metrics
• Experience operating data platforms (Snowflake, Fabric) and enterprise integration layers (MuleSoft) alongside enterprise SaaS such as D365 (F&O and/or Power Apps)
• Hands-on incident management experience with tools like Incident.io and ServiceNow, and a track record of running effective on-call and postmortem practices
• Hands-on experience building with LLMs and AI coding assistants — Cursor in particular
• Ability to define reliability strategy, reliability targets, and operational metrics — and defend them to engineering leadership and the business
• Strong communication skills — you can explain a root cause to a junior engineer and a reliability risk to a product lead
• Demonstrated bias for action and ability to operate autonomously in ambiguous, fast-changing environments