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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
Job Title: AWS DevOps Engineer
Experience Level: 5+ Years
Location: Bangalore, Pune, Hyderabad, Chennai and Gurgaon
Summary:
We are looking for a hands-on Platform Engineer with strong execution skills to provision and manage cloud infrastructure. The ideal candidate will have experience with Linux, AWS services, Kubernetes, and Terraform, and should be capable of troubleshooting complex issues in cloud and container environments.
Key Responsibilities:
- Provision AWS infrastructure using Terraform (IaC).
- Manage and troubleshoot Kubernetes clusters (EKS/ECS).
- Work with core AWS services: VPC, EC2, S3, RDS, Lambda, ALB, WAF, and CloudFront.
- Support CI/CD pipelines using Jenkins and GitHub.
- Collaborate with teams to resolve infrastructure and deployment issues.
- Maintain documentation of infrastructure and operational procedures.
Required Skills:
- 3+ years of hands-on experience in AWS infrastructure provisioning using Terraform.
- Strong Linux administration and troubleshooting skills.
- Experience managing Kubernetes clusters.
- Basic experience with CI/CD tools like Jenkins and GitHub.
- Good communication skills and a positive, team-oriented attitude.
Preferred:
- AWS Certification (e.g., Solutions Architect, DevOps Engineer).
- Exposure to Agile and DevOps practices.
- Experience with monitoring and logging tools.
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:
The company is a global leader in secure payments and trusted transactions. They are at the forefront of the digital revolution that is shaping new ways of paying, living, doing business and building relationships that pass on trust along the entire payments value chain, enabling sustainable economic growth. Their innovative solutions, rooted in a rock-solid technological base, are environmentally friendly, widely accessible and support social transformation.
- 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
- Configure, optimize, document, and support of the infrastructure components of software products (which are hosted in collocated facilities and cloud services such as AWS)
- Design and build tools and frameworks that support deployment and management and platforms
- Design, build, and deliver cloud computing solutions, hosted services, and underlying software infrastructures
- Build core functionality of our cloud-based platform product, deliver secure, reliable services and construct third party integrations
- Assist in coaching application developers on proper DevOps techniques for building scalable applications in the microservices paradigm
- Foster collaboration with software product development and architecture teams to ensure releases are delivered with repeatable and auditable processes
- Support and troubleshoot scalability, high availability, performance, monitoring, backup, and restores of different environments
- Work independently across multiple platforms and applications to understand dependencies
- Evaluate new tools, technologies, and processes to improve speed, efficiency, and scalability of continuous integration environments
- Design and architect solutions for existing client-facing applications as they are moved into cloud environments such as AWS
- Competencies
- Full understanding of scripting and automated process management in languages such as Shell, Ruby and/ or Python
- Working Knowledge SCM tools such as Git, GitHub, Bitbucket, etc.
- Working knowledge of Amazon Web Services and related APIs
- Ability to deliver and manage web or cloud-based services
- General familiarity with monitoring tools
- General familiarity with configuration/provisioning tools such as Terraform
- Experience
- Experience working within an Agile type environment
- 4+ years of experience with cloud-based provisioning (Azure, AWS, Google), monitoring, troubleshooting, and related DevOps technologies
- 4+ years of experience with containerization/orchestration technologies like Rancher, Docker and Kubernetes
· Strong knowledge on Windows and Linux
· 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

technology based supply chain management
Bachelor's degree in information security, computer science, or related.
A Strong Devops experience of at least 4+ years
Strong Experience in Unix/Linux/Python scripting
Strong networking knowledge,vSphere networking stack knowledge desired.
Experience on Docker and Kubernetes
Experience with cloud technologies (AWS/Azure)
Exposure to Continuous Development Tools such as Jenkins or Spinnaker
Exposure to configuration management systems such as Ansible
Knowledge of resource monitoring systems
Ability to scope and estimate
Strong verbal and communication skills
Advanced knowledge of Docker and Kubernetes.
Exposure to Blockchain as a Service (BaaS) like - Chainstack/IBM blockchain platform/Oracle Blockchain Cloud/Rubix/VMWare etc.
Capable of provisioning and maintaining local enterprise blockchain platforms for Development and QA (Hyperledger fabric/Baas/Corda/ETH).
About Navis
As a MLOps Engineer in QuantumBlack you will:
Develop and deploy technology that enables data scientists and data engineers to build, productionize and deploy machine learning models following best practices. Work to set the standards for SWE and
DevOps practices within multi-disciplinary delivery teams
Choose and use the right cloud services, DevOps tooling and ML tooling for the team to be able to produce high-quality code that allows your team to release to production.
Build modern, scalable, and secure CI/CD pipelines to automate development and deployment
workflows used by data scientists (ML pipelines) and data engineers (Data pipelines)
Shape and support next generation technology that enables scaling ML products and platforms. Bring
expertise in cloud to enable ML use case development, including MLOps
Our Tech Stack-
We leverage AWS, Google Cloud, Azure, Databricks, Docker, Kubernetes, Argo, Airflow, Kedro, Python,
Terraform, GitHub actions, MLFlow, Node.JS, React, Typescript amongst others in our projects
Key Skills:
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
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.
Job Dsecription: (8-12 years)
○ Develop best practices for team and also responsible for the architecture
○ solutions and documentation operations in order to meet the engineering departments quality and standards
○ Participate in production outage and handle complex issues and works towards Resolution
○ Develop custom tools and integration with existing tools to increase engineering Productivity
Required Experience and Expertise
○ Deep understanding of Kernel, Networking and OS fundamentals
○ Strong experience in writing helm charts.
○ Deep understanding of K8s.
○ Good knowledge in service mesh.
○ Good Database understanding
Notice Period: 30 day max



