11+ Logstash Jobs in Chennai | Logstash 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

AI & ML (45 Days – Live Hands‑On)

Program Fee: ₹25,000

Duration: 45 Days

Mode: Hybrid (Online Sessions + Live Lab Access)

Eligibility: Freshers, Final‑Year Students, and Career Switchers

About the Internship

This intensive 45‑day internship program is designed for freshers who want to build strong, industry‑relevant skills in Cloud Infrastructure, Cybersecurity, and AI/ML model development. The program offers live production hands‑on training, allowing interns to work on real-world architectures, security workflows, and AI/ML deployments.

Participants will receive end‑to‑end exposure to modern cloud platforms, DevOps practices, security operations, and machine learning deployment, making them job‑ready for roles like:

• Cloud/Infra Engineer
• DevOps Engineer
• Security Analyst
• AI/ML Engineer
• Site Reliability Engineer (SRE)

Key Highlights

• 45 days of practical, mentor-led training
• Live production-style projects and deployments
• Hands‑on experience with:
• AWS / Azure Cloud
• Terraform, CI/CD, Docker, Kubernetes
• Security Hardening & IAM
• Python ML pipelines & model deployment
• Architect & deploy real systems using best practices
• Build portfolio-ready projects
• Receive an industry-recognized Internship Certificate

What You Will Learn

1️⃣ Cloud Infrastructure & DevOps

• Cloud fundamentals (AWS/Azure/GCP)
• Linux administration & scripting
• VPC, Subnets, Routing, NAT, Firewalls
• EC2 provisioning & autoscaling
• Load balancing & High Availability
• Terraform for Infrastructure as Code
• CI/CD pipelines using Jenkins / GitHub Actions
• Docker containerization & Kubernetes basics

2️⃣ Cybersecurity & Cloud Security

• IAM roles, policies, access control
• Server security & hardening
• SSL/TLS, encryption, key management
• Secure VPC & subnet design
• Threat detection & logging
• Secrets management
• Network segmentation & firewall best practices

3️⃣ AI & Machine Learning

• Python for ML
• Supervised and unsupervised algorithms
• Data preprocessing & model training
• Model evaluation & optimization
• Build ML inference APIs using FastAPI/Flask
• Containerize and deploy ML models to cloud
• Integrate monitoring for ML workflows

✅ Live Hands‑On Projects

Interns will work on real-world, production-grade projects such as:

• Deploy a secure 3‑tier web application on cloud
• Automate infra provisioning using Terraform
• Build CI/CD pipelines for automated deployments
• Harden servers & configure security groups, IAM
• Develop and deploy an ML model as a cloud API
• Create monitoring dashboards with Prometheus/Grafana
• End-to-end system deployment with logging and alerting

Each intern will complete a Capstone Project and present it during the final evaluation.

✅ Internship Deliverables

1. Internship Completion Certificate
2. 3+ Production‑level projects
3. GitHub portfolio with all code and deployments
4. Cloud & ML documentation
5. Resume enhancement and guidance
6. Career mentoring + interview preparation

✅ Who Should Apply

This internship is ideal for:

• Fresh graduates
• Final‑year engineering or IT students
• BSc, BCA, MCA, B.Tech learners
• Professionals switching careers to Cloud/DevOps/AI
• Anyone seeking hands‑on, real‑time industry experience

✅ Program Fee

₹25,000/- (includes training, labs, live‑project access, certificate, and mentorship)

✅ Certificate Provided

All participants will receive a verified Internship Certificate, including:

• Candidate Name
• Internship Duration & Dates
• Skills Covered
• Project Evaluation Score
• Authorized Signatory & Company Seal

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

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

About Company:

• Role Overview

• Senior Engineer with a strong background and experience in cloud related technologies and architectures. Can design target cloud architectures to transform existing architectures together with the in-house team. Can actively hands-on configure and build cloud architectures and guide others.

• Key Knowledge

• 3-5+ years of experience in AWS/GCP or Azure technologies
• Is likely certified on one or more of the major cloud platforms
• Strong experience from hands-on work with technologies such as Terraform, K8S, Docker and orchestration of containers.
• Ability to guide and lead internal agile teams on cloud technology
• Background from the financial services industry or similar critical operational experience

Experience: 3+ years of experience in Cloud Architecture

About Company:

Cloud Architect / Lead

• Role Overview

• Senior Engineer with a strong background and experience in cloud related technologies and architectures. Can design target cloud architectures to transform existing architectures together with the in-house team. Can actively hands-on configure and build cloud architectures and guide others.

• Key Knowledge

• 3-5+ years of experience in AWS/GCP or Azure technologies
• Is likely certified on one or more of the major cloud platforms
• Strong experience from hands-on work with technologies such as Terraform, K8S, Docker and orchestration of containers.
• Ability to guide and lead internal agile teams on cloud technology
• Background from the financial services industry or similar critical operational experience

The ideal candidate is a self-motivated, multi-tasker, and demonstrated team player. You will be a lead developer responsible for the development of new software security policies and enhancements to security on existing products. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills. 

Responsibilities

• Consulting with management on the operational requirements of software solutions.
• Contributing expertise on information system options, risk, and operational impact.
• Mentoring junior software developers in gaining experience and assuming DevOps responsibilities.
• Managing the installation and configuration of solutions.
• Collaborating with developers on software requirements, as well as interpreting test stage data.
• Developing interface simulators and designing automated module deployments.
• Completing code and script updates, as well as resolving product implementation errors.
• Overseeing routine maintenance procedures and performing diagnostic tests.
• Documenting processes and monitoring performance metrics.
• Conforming to best practices in network administration and cybersecurity.

Qualifications

• Minimum of 2 years of hands-on experience in software development and DevOps, specifically managing AWS Infrastructure such as EC2s, RDS, Elastic cache, S3, IAM, cloud trail and other services provided by AWS.
• Experience Building a multi-region highly available auto-scaling infrastructure that optimises performance and cost. plan for future infrastructure as well as Maintain & optimise existing infrastructure.
• Conceptualise, architect and build automated deployment pipelines in a CI/CD environment like Jenkins.
• Conceptualise, architect and build a containerised infrastructure using Docker, Mesosphere or similar SaaS platforms.
• Conceptualise, architect and build a secured network utilising VPCs with inputs from the security team.
• Work with developers & QA to institute a policy of Continuous Integration with Automated testing Architect, build and manage dashboards to provide visibility into delivery, production application functional and performance status.
• Work with developers to institute systems, policies and workflows which allow for rollback of deployments Triage release of applications to production environment on a daily basis.
• Interface with developers and triage SQL queries that need to be executed in production environments.
• Assist the developers and on calls for other teams with post mortem, follow up and review of issues affecting production availability.
• Minimum 2 years’ experience in Ansible.
• Must have written playbook to automate provisioning of AWS infrastructure as well as automation of routine maintenance tasks.
• Must have had prior experience automating deployments to production and lower environments.
• Experience with APM tools like New Relic and log management tools.
• Our entire platform is hosted on AWS, comprising of web applications, webservices, RDS, Redis and Elastic Search clusters and several other AWS resources like EC2, S3, Cloud front, Route53 and SNS.
• Essential Functions System Architecture Process Design and Implementation

• Minimum of 2 years scripting experience in Ruby/Python (Preferable) and Shell Web Application Deployment Systems Continuous Integration tools (Ansible)Establishing and enforcing Network Security Policy (AWS VPC, Security Group) & ACLs.
• Establishing and enforcing systems monitoring tools and standards
• Establishing and enforcing Risk Assessment policies and standards
• Establishing and enforcing Escalation policies and standards

Striim (pronounced “stream” with two i’s for integration and intelligence) was founded in 2012 with a simple goal of helping companies make data useful the instant it’s born.

Striim’s enterprise-grade, streaming integration with intelligence platform makes it easy to build continuous, streaming data pipelines – including change data capture (CDC) – to power real-time cloud integration, log correlation, edge processing, and streaming analytics

2 - 5 Years of Experience in any Programming any language (Polyglot Preferred ) & System Operations • Awareness of Devops & Agile Methodologies • Proficient in leveraging CI and CD tools to automate testing and deployment . • Experience in working in an agile and fast paced environment . • Hands on knowledge of at least one cloud platform (AWS / GCP / Azure). • Cloud networking knowledge: should understand VPC, NATs, and routers. • Contributions to open source is a plus. • Good written communication skills are a must. Contributions to technical blogs / whitepapers will be an added advantage.

DevOps Consultant!! MERN Stack Project Manager – Systems (Enterprise or Solutions) Architect needed!

Hello superstar,

I appreciate you taking time to read this. I have posted a job for developers to work on a start-up, the link is ......

I would need someone with DevOps experience, to ensure that the project is undertaken with the highest standards possible. I have had many experiences where ‘completed’ software after years of development was filled with bugs and it would be more cost-effective to start from scratch than to attempt to find and correct all the bugs.

I have attempted to learn as much as possible, but I now have an opportunity and it would better serve the venture to have someone handle the management of the project to ensure that;

• We choose the most appropriate technology
• We choose competent developers in those technologies
• The architecture and data modeling are clearly defined in a ‘blueprint’ plan
• A DevOps environment and processes are set up and the developers understand what is required
• Proper tests are carried out to ensure everything works as intended
• There are processes for testers to follow and competent testers are selected to follow them
• Accessibility, localization, and internationalization are planned ahead of time
• Security, scalability, and other future probabilities that I may not even be aware of are considered and planned ahead of time
• Documentation and code reviews, refactoring and other quality assurance processes are undertaken
• Working software is produced and systems that enable new developers or teams of people to easily take over and/or contribute new modules or updates in a controlled and organized fashion
• Cost estimates or budgets/projections or use of SaaS, hosting and other 3rd party services and applications

I am more concerned with a professional and world-class organizational system than with any particular type of software been produced as the strong foundation will enable anything to be creating with efficacy and precision.

Again, thank you for reading this, please reply with the word “superstar” anywhere in the second line of your response.  I look forward to hearing from you.

Warm wishes DevOps Evangelist,