Live opening · Posted 9 hours ago

DevOps Engineer

Nestingale · India (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 9 hours ago
CompanyNestingale
LocationIndia (Remote)
Work modeYes
SkillsPython, AWS, Azure, GCP, Docker, Kubernetes, Terraform
SourceLinkedin
ListedPosted 9 hours ago

About the role

Description supplied by the original job listing.

About the job
Headline: DevOps Engineer (AI-Native Track)
Location: Remote, Bangalore & Hyderabad area — to reach a nearby office occasionally
Joining: Immediate
About the engagement
You will be working as part of the Nestingale delivery team: running CI/CD and cloud infrastructure for production systems, and growing into the engineer who builds and operates the infrastructure behind applied-AI — LLM/RAG and GenAI — workloads. Hands-on platform engineering that takes services from build to reliable production — and, over your first year, from conventional DevOps to AI-native. Not research, not advisory.
What you’ll do
Build and run CI/CD pipelines and cloud infrastructure end to end (IaC, containers, deploys, monitoring)
Keep production healthy — reliability, latency, cost, security, incident response
Stand up the infra behind AI workloads — model serving, inference pipelines, GPU provisioning, evals and observability
Partner with product/eng to automate operations, increasingly with AI agents and copilots
Who you are
3–5 years hands-on in DevOps, SRE, platform, or cloud engineering
Real IaC (Terraform or equivalent) and a major cloud (GCP/AWS/Azure) — not just clicking consoles
Hands-on with Docker + Kubernetes and CI/CD; scripting in Python, Go, or Bash
Think in systems, latency, and cost; enjoy debugging why something is slow, flaky, or expensive — and genuinely want to grow into AI-native work
Must have
Demonstrated production experience — you’ve built and operated infrastructure real users depend on and can walk us through it in detail — with strong IaC, containers, and CI/CD, and a real appetite for AI-native engineering (MLOps/LLMOps, agentic automation, AI cost & governance).
Technical stack
Terraform, Docker, Kubernetes · CI/CD (GitHub Actions / GitLab CI) · cloud (GCP/AWS), Git · Python/Go/Bash · nice to have: MLOps/LLMOps (Vertex AI, MLflow, LangChain, vector DBs), GPU infra, FinOps

Work arrangement
Yes

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