DevOps Engineer at Zocket · Chennai · 1 - 3 years · ₹5L - ₹12L / yr · Raised funding · Posted 21 May 2026
Amazon Web Services (AWS)
Jenkins
Kubernetes
GitHub
DockerWhy this role exists
Our infrastructure footprint is growing faster than our headcount, and we believe most of that
gap should be closed by automation and AI agents — not by hiring more humans to do toil. We
need someone early in their career who treats manual work as a bug, ships scripts and agents
instead of tickets, and wants to grow into deeper ownership over the next two years.
You will not be the most senior person on the team. You will be the one who multiplies the team.
What you'll own
In your first 1 months
• Take ownership of one slice of our CI/CD pipeline and make it measurably
faster, more reliable, or cheaper. We expect a number on a dashboard to move.
• Build at least three internal automations that replace manual ops toil —
using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force
multiplier.
• Be the first responder for a defined set of alerts. Write the runbooks. Drive
the alert volume down.
• Support senior engineers on AI/ML infrastructure (GPU nodes, inference
services, model deployment) — observe, document, and gradually take on contained
changes under review.
By 3 months you should be
• The go-to person for at least two production systems.
• Shipping routine infrastructure changes without needing senior review.
• Treating "manual" as a code smell.
Required (we will reject without these)
• 0–3 years hands-on experience with one major cloud (AWS, GCP, or
Azure — one is fine, depth beats breadth).
• Fluent in Linux command line, bash, and at least one scripting language
(Python or Go preferred).
• Have shipped something to production that real users hit. A side project
counts; a graded coursework lab does not.
• Comfortable with Docker — you can explain what an image vs. a
container is and why it matters.
• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,
TLS, ports, basic subnets — enough to debug "it works on my machine."
• Git fluency: branches, merges, rebases, conflict resolution.
• CI/CD pipelines — you have authored or substantially modified pipelines
in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."
• Kubernetes basics — kubectl for real work, can read pod logs,
understand deployments and services, can debug a CrashLoopBackOff without
panicking. You do not need to have run a cluster; you do need to have lived inside one.
• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic
CLIs, etc.). You should be able to walk us through specific tasks where they made you
faster, and specific tasks where they failed you and how you noticed. "I have tried it" is
not enough.
Bonus (real plus, not required)
• Infrastructure as Code: Terraform, Pulumi, or Ansible.
• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.
• Have built or extended an LLM-based agent — a custom MCP server, a
scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond
chat-with-Claude.
• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or
ML pipelines.
What we don't care about
• Whether your degree is in CS — or whether you have a degree at all.
• Brand-name companies on your resume.
• Certifications. They are fine. They do not substitute for having shipped.
How we work
• We default to automation. If you do something manually twice, the third
time you script it or hand it to an agent.
• AI agents are part of the workflow, not a novelty. Expect interview
questions about exactly how you use them — and where you have caught them being
wrong.
• Small, reversible changes beat big-bang rollouts.
• Postmortems are blameless and written down.
• We push back on each other. If you only execute, you will be unhappy
here.
How to apply
Send:
• Your resume.
• A short note (≤200 words) describing one infra or automation problem you
solved, and how AI agents factored in — or did not, and why. We read these. Generic
notes get rejected.
Internal note — delete before posting externally
• Comp band, location policy, team name, and reporting line marked
[CONFIRM] need to be filled in before this goes external.
• The Required list is intentionally tight: CI/CD and Kubernetes basics
promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The
remaining pool will skew toward people who have actually shipped infra at a startup, not
bootcamp grads or pure cloud-cert holders.
• IaC, observability, agent-building, and GPU/ML serving stay as bonus.
Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces
hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5
yrs) and raise the band.
• Screening implication: the resume screen should explicitly check for
CI/CD pipeline authorship and any K8s-touching production work. If neither is on the
resume, reject at screen. Do not waste interview slots.
• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of
active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and
screen for it in interview instead). Do not relax the "shipped to production" requirement
— that is the load-bearing filter.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Zocket
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Amazon Web Services (AWS)The Role
As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that
keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and
observability that let a small, fast-moving team ship confidently — and you'll keep our AI and
data workloads reliable and affordable at scale.
This is a hands-on role with real ownership: you won't be maintaining someone else's setup,
you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make
deployment boring, incidents rare, and scaling a non-event. ---
What You'll Own
**CI/CD & developer experience**
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confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible
automated testing, rollbacks, and release controls.
**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or
similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow.
**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and
resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch
processing for the speech pipeline.
**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting,
on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients.
**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and
processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware.
**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in
transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security
requirements) for a product that handles sensitive customer conversations.
**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability
and spend. ---
What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production
systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and
Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI,
Jenkins, Argo, or similar).
- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong
automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog,
OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team.
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pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data
pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud
ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. ---
Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real
scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data,
and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an
DockerKubernetesAmazon Web Services (AWS)We are seeking a highly skilled and experienced DevOps Engineer to join our development team.
Years of experience needed: 8+ Yrs
Required Skills
Strong experience with GitLab, TeamCity, Terraform, Kubernetes and Docker
Proficiency in various deployment strategies and CI/CD pipeline setups
Solid understanding of Linux administration and Windows IIS.
Advanced scripting skills in bash and PowerShell
Hands-on experience with Google Cloud Platform (GCP) services, particularly GKE, GCS, GCE, Cloud SQL, and load balancers
Familiarity with Autosys for job scheduling and automation
Excellent problem-solving and troubleshooting skills
Ability to work independently and collaboratively in a fast-paced environment
- • Strong communication and interpersonal skills.
Build production-grade cloud infrastructure that powers enterprise applications with cutting-edge DevOps practices.
What you'll do:
- Design CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI)
- Containerize apps with Docker, deploy on Kubernetes clusters
- Manage infrastructure as code (Terraform, CloudFormation)
- Set up monitoring (Prometheus, Grafana, ELK Stack)
- Cloud migrations (AWS EC2, EKS, RDS → GCP equivalent)
- Optimize costs and performance for live production systems
What we need:
- Basic Python/Bash scripting
- Docker basics, Git workflows
- Cloud exposure (AWS/GCP/Azure free tier projects)
- Problem-solving mindset, eagerness to learn
Real impact:
- Deploy apps used by 1000+ daily users
- Work with senior DevOps engineers on client deliverables
- Build portfolio for FAANG-level interviews
We are looking for an experienced DevOps Engineer with strong expertise in Linux, CI/CD, containerization, cloud platforms, Infrastructure as Code (IaC), and observability. The ideal candidate should have hands-on experience with Kubernetes, OpenShift, Terraform, scripting, DevSecOps, and modern monitoring practices.
Responsibilities:
- Manage and maintain Linux-based systems, cloud infrastructure, and production environments.
- Develop, maintain, and optimize CI/CD pipelines using Git and related automation tools.
- Deploy and manage containerized applications using Docker, Kubernetes (K8s), and OpenShift.
- Provision and manage cloud infrastructure on AWS and/or Microsoft Azure.
- Automate infrastructure provisioning and configuration using Terraform.
- Develop automation scripts using Python and Shell scripting.
- Implement observability and monitoring solutions using Prometheus, Grafana, AppDynamics, and Splunk.
- Troubleshoot production incidents, perform root cause analysis (RCA), and improve system reliability and availability.
- Implement DevSecOps practices, security controls, and vulnerability management across CI/CD pipelines.
- Manage cloud networking, connectivity, and infrastructure-related configurations.
- Support AIOps initiatives to improve incident detection, analysis, and operational efficiency.
- Manage SSL/TLS certificates, secrets, and secure credential rotation.
Required Skills:
- Strong hands-on experience with Linux.
- Good knowledge of Git and CI/CD pipelines.
- Experience with Docker, Kubernetes (K8s), and/or OpenShift.
- Working experience with AWS and/or Microsoft Azure.
- Hands-on experience with Terraform and Infrastructure as Code (IaC).
- Scripting knowledge in Python and/or Shell.
- Experience with Prometheus, Grafana, AppDynamics, and/or Splunk.
- Knowledge of DevSecOps, networking, and cloud security fundamentals.
- Understanding of AIOps concepts and automated operations.
- Experience with certificate lifecycle management and secrets management.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon