11+ Kibana Jobs in Chennai | Kibana Job openings in Chennai

DESIRED SKILLS AND EXPERIENCE

 Strong analytical and problem-solving skills

 Ability to work independently, learn quickly and be proactive

 3-5 years overall and at least 1-2 years of hands-on experience in designing and managing DevOps Cloud infrastructure

 Experience must include a combination of:

o Experience working with configuration management tools – Ansible, Chef, Puppet, SaltStack (expertise in at least one tool is a must)

o Ability to write and maintain code in at least one scripting language (Python preferred)

o Practical knowledge of shell scripting

o Cloud knowledge – AWS, VMware vSphere o Good understanding and familiarity with Linux

o Networking knowledge – Firewalls, VPNs, Load Balancers

o Web/Application servers, Nginx, JVM environments

o Virtualization and containers - Xen, KVM, Qemu, Docker, Kubernetes, etc.

o Familiarity with logging systems - Logstash, Elasticsearch, Kibana

o Git, Jenkins, Jira

Applicants must read the JD and understand the JD throughly

Job Title: Database & DevOps Engineer

Location: Chennai, Tamil Nadu (On-site/Hybrid)

Experience: 2+ years -

Job Summary

We are looking for a skilled Database & DevOps Engineer with 2+ years of hands-on experience in database administration, cloud infrastructure, CI/CD pipelines, automation, and AI application deployment. The role involves managing database and infrastructure environments, automating deployments, supporting AI/LLM workloads, and ensuring high availability, security, performance, and scalability.

Key Responsibilities

Database Management

• Install, configure, monitor, and maintain SQL and NoSQL databases.

• Manage database backup, recovery, replication, and disaster recovery.

• Optimise performance through indexing, query tuning, and monitoring.

• Ensure database security, integrity, and availability.

• Troubleshoot database issues and provide timely resolutions.

DevOps, Infrastructure & AI Operations

• Design, implement, and maintain CI/CD pipelines.

• Automate infrastructure provisioning using Infrastructure as Code tools.

• Deploy and manage applications across cloud and on-premises environments.

• Configure and maintain containerised applications using Docker and Kubernetes.

• Deploy and support AI/ML, LLM, RAG, and agentic AI applications.

• Configure and manage GPU-enabled infrastructure for AI workloads.

• Support model serving, vector databases, and AI application APIs.

• Monitor application, infrastructure, and AI-service performance, including availability, latency, resource utilization, and failures.

• Maintain Linux servers and automate routine operational tasks.

• Implement secure management of credentials, secrets, model endpoints, and data access.

• Collaborate with development and AI teams to streamline deployment and release processes.

Mandatory Skills

• 2+ years of hands-on experience in Database Administration and DevOps.

• Strong knowledge of MySQL, PostgreSQL, Microsoft SQL Server, and MongoDB.

• Experience with database backup, restoration, replication, indexing, query optimization, and performance monitoring.

• Hands-on experience with Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps.

• Experience with Docker and Kubernetes.

• Experience with AWS, Azure, or GCP.

• Knowledge of Terraform and Ansible.

• Strong Linux administration and shell-scripting skills.

• Experience with Prometheus, Grafana, ELK Stack, or Nagios.

• Working knowledge of networking, security, SSL/TLS, and load balancing.

• Understanding of LLMs, RAG, embeddings, vector databases, and agentic AI architecture.

• Experience deploying Python-based AI/ML services and APIs.

• Familiarity with model-serving tools such as llama.cpp, vLLM, Ollama, Hugging Face, or equivalent.

• Knowledge of GPU-enabled environments, NVIDIA drivers, CUDA, and containerized AI deployment.

• Understanding of AI/LLM observability, model versioning, security, scaling, and rollback.

• Strong troubleshooting, analytical, and problem-solving skills.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline.

• Cloud, DevOps, Linux, database, or Kubernetes certifications are an advantage.

Technical Stack

• Databases: MySQL, PostgreSQL, Microsoft SQL Server, MongoDB and vector databases

• Cloud: AWS, Azure, GCP.

• CI/CD: Jenkins, GitLab CI/CD, Azure DevOps

• Containers and IaC: Docker, Kubernetes, Terraform, Ansible

• Monitoring: Prometheus, Grafana, ELK Stack, Nagios

• AI Infrastructure: Python APIs, LLM serving, RAG, embeddings, vector search, GPU/CUDA

• Operating Systems: Linux—Ubuntu, CentOS, Red Hat

Soft Skills

• Excellent communication and collaboration skills.

• Strong ownership and accountability.

• Ability to work effectively in a fast-paced Agile environment.

• Proactive approach to troubleshooting and continuous improvement.

• Ability to manage multiple priorities and deliver on time.

Why 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.

Greetings!

Wissen Technology is hiring for Kubernetes Lead/Admin.

Required:

• 7+ years of relevant experience in Kubernetes
• Must have hands on experience on Implementation, CI/CD pipeline, EKS architecture, ArgoCD & Statefulset services.
• Good to have exposure on scripting languages
• Should be open to work from Chennai
• Work mode will be Hybrid

Company profile:

Company Name : Wissen Technology

Group of companies in India : Wissen Technology & Wissen Infotech

Work Location - Bangalore

Website : www.wissen.com

Wissen Thought leadership : https://www.wissen.com/articles/

LinkedIn: https://www.linkedin.com/company/wissen-technology

The candidates should have:

·  Strong knowledge on Windows and Linux OS

·   Experience working in Version Control Systems like git

·  Hands-on experience in tools Docker, SonarQube, Ansible, Kubernetes, ELK.

·  Basic understanding of SQL commands

·  Experience working on Azure Cloud DevOps

DevOps Architect 

Experience:  10 - 12+ year relevant experience on DevOps
Locations : Bangalore, Chennai, Pune, Hyderabad, Jaipur.

Qualification:
• Bachelors or advanced degree in Computer science, Software engineering or equivalent is required.
• Certifications in specific areas are desired

Technical Skillset: Skills Proficiency level

• Build tools (Ant or Maven) - Expert
• CI/CD tool (Jenkins or Github CI/CD) - Expert
• Cloud DevOps (AWS CodeBuild, CodeDeploy, Code Pipeline etc) or Azure DevOps. - Expert
• Infrastructure As Code (Terraform, Helm charts etc.) - Expert
• Containerization (Docker, Docker Registry) - Expert
• Scripting (linux) - Expert
• Cluster deployment (Kubernetes) & maintenance - Expert
• Programming (Java) - Intermediate
• Application Types for DevOps (Streaming like Spark, Kafka, Big data like Hadoop etc) - Expert
• Artifactory (JFrog) - Expert
• Monitoring & Reporting (Prometheus, Grafana, PagerDuty etc.) - Expert
• Ansible, MySQL, PostgreSQL - Intermediate

• Experience working on Linux based infrastructure
• Strong hands-on knowledge of setting up production, staging, and dev environments on AWS/GCP/Azure
• Strong hands-on knowledge of technologies like Terraform, Docker, Kubernetes
• Strong understanding of continuous testing environments such as Travis-CI, CircleCI, Jenkins, etc.
• Configuration and managing databases such as MySQL, Mongo
• Excellent troubleshooting
• Working knowledge of various tools, open-source technologies, and cloud services
• Awareness of critical concepts in DevOps and Agile principles