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Bengaluru, Karnataka, India
Remote only
We're hiring a Staff Engineer to join JumpCloud's Cloud Platform organization, with a focus on observability and FinOps.
You'll own the questions that matter most as we scale toward 99.99% availability: can we see what's happening across the platform, how fast do we recover when something breaks, can we survive a regional outage, and are we spending enough to run it all? This is a hands-on staff role. You'll set the technical direction for observability, incident management, disaster recovery, and cloud cost, write the code and AI-driven automation that make it real, and work closely with engineering, customer support, finance, and leadership.
Observability
Set the technical direction for observability across JumpCloud's cloud platform: metrics, logs, traces, and events, on AWS and GCP.
Build and run our observability stack (Datadog, Prometheus, Grafana, OpenTelemetry), including standard instrumentation libraries and collectors that teams adopt by default.
Define SLIs, SLOs, and error budgets with service owners, and build the dashboards and burn-rate alerts that hold us to a 99.99% SLA.
Cut alert noise. Make sure every page is actionable, routed to the right owner, and backed by a runbook.
Shorten detection and recovery times (MTTD and MTTR) by improving tracing, correlation, and incident tooling.
Manage observability cost itself: cardinality, log volume, sampling, and retention, so visibility grows without the bill growing with it.
FinOps
Own cloud cost visibility: tagging standards, cost allocation by team and service, and showback reports that engineers actually read.
Find and deliver savings through right-sizing, autoscaling, spot capacity, storage tiering, idle-resource cleanup, and data-transfer reduction.
Shape our commitment strategy (Savings Plans, Reserved Instances, committed-use discounts) with finance, based on real usage data.
Build automation and guardrails, such as budget alerts, anomaly detection, and policy-as-code checks, that catch waste before it ships.
Define unit economics, like cost per customer or per device, and make cost a normal input to design reviews.
Partner with finance on forecasting and budgeting, and explain cloud spend clearly to leadership.
Incident Management and AI-Driven Automation
Own the incident management process end to end: severity levels, on-call rotations, escalation paths, communication, and the tooling behind them.
Lead major incidents as incident commander or senior escalation point, and keep customers and leadership informed.
Run root cause analysis (RCA) for significant incidents, and drive the follow-up actions to completion so issues don't repeat.
Build AI agents that correlate alerts, logs, traces, and recent changes to find the likely root cause automatically.
Build self-healing automation and AI agents that detect and fix known issues before they escalate or reach customers, with safe guardrails and human approval where it matters.
Measure and improve incident health over time: MTTD, MTTR, repeat incidents, and on-call load.
Business Continuity and Disaster Recovery
Own JumpCloud's business continuity (BCP) and disaster recovery (DR) strategy for the cloud platform.
Define RTO and RPO targets with product and leadership, and design the architecture to meet them.
Design and build the DR site and recovery environment across AWS and GCP, including data replication, backups, failover, and failback.
Plan and run regular DR tests and failover drills, document the results, and close the gaps they reveal.
Keep DR runbooks, recovery automation, and BCP plans current, and support audit and customer requests for evidence.
Across Everything
Write production-quality Go or Python for tooling, exporters, data pipelines, and automation.
Work closely with customer support teams: turn support tickets and escalations into monitoring, alerts, and fixes, and give support the visibility they need to answer customers quickly.
Partner with product engineering teams on reliability, recoverability, and cost-aware design.
Write design docs, review architecture across engineering, and mentor engineers on observability and cost-aware design.
10+ years of software engineering experience, with at least 4 years in platform, SRE, or infrastructure roles running 24/7 SaaS systems at scale.
Observability depth: You've designed and run observability at scale with Datadog, Prometheus, Grafana, or OpenTelemetry. You know how to instrument services, set meaningful SLOs, and build alerts people trust.
FinOps track record: You've cut cloud spend in a measurable way, and you can show the numbers. You're comfortable with AWS Cost Explorer, CUR, Kubecost, or similar tools, and with commitment planning.
Strong coding skills: You've built production tooling and automation in Go or Python, not just dashboards and scripts.
AWS, GCP, and Terraform: strong hands-on production experience with both AWS and GCP, and with Terraform for infrastructure as code. Production Kubernetes experience is expected.
Incident management: You've owned on-call and incident processes, led major incidents, and run RCAs that led to lasting fixes.
AI and automation: You've built automation for incident response or remediation, and you have hands-on experience building AI agents or LLM-based tools for root cause analysis or auto-remediation.
BCP and DR: You've designed and tested disaster recovery for production SaaS systems, including RTO and RPO targets, DR sites, replication, and failover drills.
Engineering and customer focus: You have a software engineering background and have worked closely with customer support teams to resolve issues and reduce customer impact.
Staff-level influence: You've driven change across multiple teams without direct authority, and you can get engineers to care about both reliability and cost.
Clear communication with engineers, finance, and leadership. You can turn usage and cost data into a simple story and a clear decision.
Bachelor's degree in Computer Science or a related field, or equivalent experience.
A strong team player who lives our core values: building connections, thinking big, and getting 1% better every day.
FinOps Certified Practitioner, or hands-on experience applying the FinOps Framework.
Experience with cost tools such as CloudHealth, Vantage, Cloudability, or AWS Compute Optimizer.
Experience building cost and usage data pipelines (AWS CUR, BigQuery billing export, Athena) and reporting on top of them.
Experience running observability in-house at scale (Prometheus/Thanos/Mimir, Loki, Tempo) and weighing that against SaaS vendors.
Experience with eBPF-based monitoring, continuous profiling, or real user monitoring.
Experience negotiating or managing vendor contracts for observability or cloud spend.
Open-source contributions, published writing, or conference talks on observability or FinOps.