The Role The Site Reliability Engineer keeps a real-time customer decisioning platform for a leading UK telecoms group reliable in production. The platform decides which offer, message or next step each customer sees, across three consumer brands and every channel, so an outage or a slow response reaches customers at once.

You'll set and track service objectives, build the monitoring and alerting the team relies on, lead incident response and make releases safe. The role is based in India. You'll be part of an on-call rota and support production releases, which run late in the evening UK time and so at night in India. You'll make operations AI-operated by design: agents that triage alerts, read logs and traces, and draft incident timelines and runbooks, while a person approves anything that changes production.

This is a client-facing consulting role requiring confident engagement with client stakeholders, calm judgement under pressure, and the credibility to stop a release that isn't safe.

What the role owns.

Production reliability: service level objectives and error budgets, monitoring and alerting, incident response and post-incident reviews, the on-call rota, release support and rollback readiness, and capacity and resilience. The DevOps Engineer owns the delivery platform, and you work as one team with them.

The Lead Technical

Consultant owns architecture and technical risk, and you contribute through ADRs.

The Agentic Delivery

Manager coordinates releases and tracks incidents and defects with you. Product engineers own their services in production, and you make that safe.

What we expect of everyone. Every role on this team, consultant or engineer, works with a product engineering mindset and an AI engineering mindset. You own the outcome, not the ticket: you understand the business problem, shape the requirement, make and record the decision, ship in small steps and check the result in production.

AI is part of how you work, not a side project:



you use AI assistants and agents every day, build with them where they help, check what they produce and share what works.

Key Accountabilities

- Take your turn on the on-call rota, respond to production alerts and incidents out of hours, and escalate early with options.
- Support late-night production releases: readiness checks, live monitoring during and after deployment, release verification and quick rollback.
- Lead incident response: triage, mitigation, communication and restoring service, then run blameless post-incident reviews and see the actions through.
- Define service level indicators and objectives with product engineers and the client, and track error budgets.
- Build logs, metrics, traces, dashboards and alerts that someone acts on, and remove noisy alerts.
- Write and maintain runbooks, and automate the steps that repeat.
- Build AI agents into operations with the AI Technical Consultant, such as alert triage, log and trace analysis, incident timelines and runbook drafting, with human approval for any change to production.
- Run production readiness reviews for new services and major changes.
- Test capacity, performance and resilience, including failure and recovery exercises.
- Work with the DevOps Engineer on safe deployment, such as feature flags, canary rollout and automated verification, and on the move from AWS to GCP with operational parity.
- Track recurring incidents and defects with the Agentic Delivery Manager and Product Support, and feed the lessons back to the engineers.
- Keep Kafka, PostgreSQL and the services around them healthy, with the engineers who own them.




- Write ADRs for significant reliability decisions and take part in the weekly ADR review.

Strong candidates may come from roles such as:

- 6-10 years of Production or application support engineers who have moved into site reliability engineering.
- DevOps or platform engineers who have carried an on-call rota for customer-facing services.
- Backend engineers who have owned their services in production, including out of hours.
- Operations or command-centre engineers who have automated their way into engineering.
- Consultancy engineers who have run managed services or round-the-clock support for clients.

Useful Experience

- OpenTelemetry, and incident tooling such as PagerDuty or Opsgenie.
- Chaos engineering, failure testing or disaster-recovery exercises.
- Kafka operations, PostgreSQL performance and JVM tuning.
- GitLab CI/CD and progressive delivery.
- Enterprise change and incident processes, including release trains.
- Moving workloads from AWS to GCP, with operational-parity validation.
- Certifications are welcome but not required: we weigh evidence over badges.

What success looks like

These outcomes describe what good looks like in the role. They are not additional CV screening requirements.

First 90 days

- You're on the on-call rota, with runbooks you trust for the services you cover.
- Every release in your window has readiness checks, live monitoring and a rollback plan.
- Alert noise is down, and every alert that pages someone has an owner and a runbook.
- An AI agent helps with triage or incident write-ups, with a named human check.

First six months

- Service objectives agreed and tracked for the most critical services, with error budgets in use.
- Time to restore service improves against your 90-day baseline.
- Repeat incidents fall, because post-incident actions close.
- Releases go out without surprises, and a rollback, when needed, works first time.

📌 Site Reliability Engineer (Bengaluru)
🏢 Moolya
📍 Bengaluru