Salary
≈ $29k – $73k per year (Estimated)
Location
Remote/Hybrid (Bengaluru, India)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
We're building revolutionary identity and security solutions to help the world's largest companies migrate to the cloud and solve the toughest security challenges in record time. What's our secret? Our people. We're a global group of innovators wh...
We’re a fast-moving AI Security Company building AI-native infrastructure and applications powered by LLMs and autonomous agents. Our stack is deeply integrated with AWS, Kubernetes, and OpenAI-based systems, and we’re rethinking reliability in a world where software can reason, adapt, and self-heal.
We’re hiring a Senior SRE Engineer to own reliability across our cloud-native and AI-driven platform. You’ll work at the intersection of distributed systems, Kubernetes operations, and LLM-powered automation, building systems that don’t just scale-but think and fix themselves.
WHAT YOU BRING
- 5+ years in SRE / DevOps / Platform Engineering.
- Strong hands-on experience with:
- AWS infrastructure at scale
- Kubernetes (production-grade clusters)
- Proven ability to debug complex distributed systems under pressure.
- Strong coding skills (Python or Go)-you build internal platforms and tools.
- Experience implementing monitoring, alerting, and incident management systems.
- Experience working with LLM APIs such as the OpenAI API.
- Familiarity with agent frameworks like:
- LangChain
- AutoGen
- Built or experimented with:
- AI agents for DevOps / SRE workflows
- Retrieval-Augmented Generation (RAG) systems
- Vector databases (Pinecone, Weaviate, etc.)
- Exposure to AIOps or intelligent automation systems.
Bonus (AI / LLM Focus)
WHAT YOU WILL BE DOING
- Own uptime, reliability, and performance of services running on AWS + Kubernetes (EKS).
- Design and implement self-healing infrastructure using automation and AI agents.
- Build LLM-powered operational tooling using APIs such as the OpenAI API for:
- Intelligent alert triage
- Incident summarization
- Root cause analysis
- Runbook automation
- Manage and scale Kubernetes workloads:
- Deployments, autoscaling, resource optimization
- Cluster reliability and cost efficiency
- Build and evolve observability systems:
- Metrics (Prometheus), dashboards (Grafana)
- Logs (ELK / OpenSearch)
- Tracing (OpenTelemetry)
- Define and enforce SLOs, SLAs, and error budgets tied to business metrics.
- Automate infrastructure using Terraform and CI/CD pipelines.
- Lead incident response, postmortems, and continuous reliability improvements.
- Introduce chaos engineering practices to proactively test system resilience.
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