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. 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.

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. Product engineers own their services in production, and you make that safe.

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.

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.
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.
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.

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.
- Useful Experience

Chaos engineering, failure testing or disaster-recovery exercises.
Kafka operations, PostgreSQL performance and JVM tuning.
Moving workloads from AWS to GCP, with operational-parity validation.
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.
An AI agent helps with triage or incident write-ups, with a named human check.

📌 Site Reliability Engineer - Midnight (Bengaluru)
🏢 Moolya Software Testing
📍 Bengaluru