Most systems don’t fail because of one big outage.
They fail because reliability is treated as an afterthought.
Right now, uptime depends too much on individual heroics.
That doesn’t scale.
This role exists to build a reliability system where:
- Uptime is predictable
- Failures are contained
- Escalations don’t depend on leadership
What you’ll do
You will not just monitor systems.
You will own reliability as a product.
1. Drive uptime to production-grade reliability
- Improve system uptime to 99.9% customer-facing SLA within 4 months
- Define and track:
- SLAs / SLOs / error budgets
- Ensure reliability is measured from the customer’s perspective, not internal metrics
2. Build incident response as a system
- Set up a 24/7 incident response rotation across 3 engineers
- Eliminate dependency on leadership (no single escalation point)
- Define:
- Incident severity levels
- Response playbooks
- Escalation protocols
- Ensure rapid detection → containment → resolution
3. Contain and fix erratic system behavior
- Identify and resolve:
- Latency spikes
- Downtime incidents
- Integration failures
- Build guardrails to prevent recurrence
- Focus on root cause elimination, not temporary fixes
4. Create continuous reliability feedback loops
- Work closely with engineering teams to:
- Surface recurring failure patterns
- Improve build quality
- Reduce production bugs
- Ensure learnings from incidents directly improve future releases
5. Improve observability and monitoring
- Build dashboards and alerts for:
- System health
- Performance metrics
- Failure signals
- Ensure issues are detected before customers report them
6. Reduce operational fragility
- Remove single points of failure (people, systems, workflows)
- Improve system resilience across:
- Deployments
- Integrations
- Runtime environments
What success looks like
- Uptime reaches 99.9%+ reliably
- Incidents are:
- Detected early
- Contained quickly
- Resolved permanently
- No dependency on a single individual for escalation
- System behavior becomes predictable and stable
- Engineering teams ship with higher reliability confidence
Who you are
- You have 2-5 years of experience in SRE / DevOps / backend systems
- You have worked on production systems with real uptime expectations
- You think in:
- Systems
- Failure modes
- Trade-offs
- You are comfortable debugging live, high-pressure environments
What will make you stand out
- Experience with:
- Distributed systems
- Cloud infrastructure (AWS / Azure / GCP)
- Monitoring & alerting tools
- Have built or improved:
- Incident response systems
- Reliability frameworks
- Strong debugging skills across:
- Infra
- Application
- Integrations
Compensation
₹60,000/month (fixed)
(Aligned with role scope and impact expectations)
Why join
- You will define reliability standards for a production AI platform
- Your work directly impacts:
- Customer trust
- Product performance
- Enterprise readiness
- You will move the system from reactive → predictable
What this role is not
- Not just monitoring dashboards
- Not limited to handling tickets
- Not dependent on escalation to leadership
What this role is
- A builder of reliability systems
- A guardian of uptime and performance
- A multiplier of engineering quality
One question to self-evaluate
Can you build a system where downtime is rare, predictable, and never dependent on a single person?
Skills:- DevOps, Amazon Web Services (AWS), Google Cloud Platform (GCP) and Windows Azure