
We are seeking experienced Mainframe Z/OS System Programmer/Admin to manage z/OS environments.
Job Title - Mainframe z/OS System Programmer
Experience - 4-8 Years
Location - Bangalore, Chennai, Pune [Hybrid/Remote]
Notice Period - Immediate Joiners Preferred
Job Overview
We seek an experienced Mainframe z/OS System Programmer to manage and support z/OS environments. The role includes system upgrades, performance monitoring, installations, troubleshooting, and expertise in ISV tools, JCL, scripting, and system utilities.
Key Responsibilities
- Administer and support z/OS mainframe systems.
- zOS install and upgrade, PTF patch apply
- ISV tools installation and upgrade
- Parmlib, Proclib
- Perform SMP/E & Non-SMP/E installation of ISV products and manage upgrades (z/OS V2.5/V3.1).
- Configure and manage JES3/JES2, Sysplex, and related components.
- Configure and monitor TSO/E, ISPF, and basic scripting in REXX/CLIST.
- Plan and execute z/OS upgrade and maintenance roadmaps.
- Monitor system performance using tools like SMF and z/OS Health Checker.
- Support mainframe storage management (SMS/DFSMS) and backup/recovery processes.
- Resolve incidents using appropriate tools and perform diagnostics as required.
- Candidates with prior experience as a z/OS System Programmer, specializing exclusively in z/OS administration, are encouraged to apply.
Preferred Technical Skills
1. Mainframe zOS Admin
2. zOS install and upgrade, PTF patch apply
3. ISV tools installation and upgrade
4. Parmlib, Proclib
Note
The candidate must have prior experience working as a z/OS System Programmer with hands-on expertise in managing complex mainframe environments.

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Senior Cloud Engineer Job Description
Position Title: Senior Cloud Engineer -- AWS [LONG TERM-CONTRACT POSITION]
Location: Remote [REQUIRES WORKING IN CST TIME ZONE]
Position Overview
The Senior Cloud Engineer will play a critical role in designing, deploying, and managing scalable, secure, and highly available cloud infrastructure across multiple platforms (AWS, Azure, Google Cloud). This role requires deep technical expertise, leadership in cloud
strategy, and hands-on experience with automation, DevOps practices, and cloud-native technologies. The ideal candidate will work collaboratively with cross-functional teams to deliver robust cloud solutions, drive best practices, and support business objectives
through innovative cloud engineering.
Key Responsibilities
Design, implement, and maintain cloud infrastructure and services, ensuring high availability, performance, and security across multi-cloud environments (AWS, Azure, GCP)
Develop and manage Infrastructure as Code (IaC) using tools such as Terraform, CloudFormation, and Ansible for automated provisioning and configuration
Lead the adoption and optimization of DevOps methodologies, including CI/CD pipelines, automated testing, and deployment processes
Collaborate with software engineers, architects, and stakeholders to architect cloud-native solutions that meet business and technical requirements
Monitor, troubleshoot, and optimize cloud systems for cost, performance, and reliability, using cloud monitoring and logging tools
Ensure cloud environments adhere to security best practices, compliance standards, and governance policies, including identity and access management, encryption, and vulnerability management
Mentor and guide junior engineers, sharing knowledge and fostering a culture of continuous improvement and innovation
Participate in on-call rotation and provide escalation support for critical cloud infrastructure issues
Document cloud architectures, processes, and procedures to ensure knowledge transfer and operational excellence
Stay current with emerging cloud technologies, trends, and best practices,
Required Qualifications
- Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent work experience
- 6–10 years of experience in cloud engineering or related roles, with a proven track record in large-scale cloud environments
- Deep expertise in at least one major cloud platform (AWS, Azure, Google Cloud) and experience in multi-cloud environments
- Strong programming and scripting skills (Python, Bash, PowerShell, etc.) for automation and cloud service integration
- Proficiency with DevOps tools and practices, including CI/CD (Jenkins, GitLab CI), containerization (Docker, Kubernetes), and configuration management (Ansible, Chef)
- Solid understanding of networking concepts (VPC, VPN, DNS, firewalls, load balancers), system administration (Linux/Windows), and cloud storage solutions
- Experience with cloud security, governance, and compliance frameworks
- Excellent analytical, troubleshooting, and root cause analysis skills
- Strong communication and collaboration abilities, with experience working in agile, interdisciplinary teams
- Ability to work independently, manage multiple priorities, and lead complex projects to completion
Preferred Qualifications
- Relevant cloud certifications (e.g., AWS Certified Solutions Architect, AWS DevOps Engineer, Microsoft AZ-300/400/500, Google Professional Cloud Architect)
- Experience with cloud cost optimization and FinOps practices
- Familiarity with monitoring/logging tools (CloudWatch, Kibana, Logstash, Datadog, etc.)
- Exposure to cloud database technologies (SQL, NoSQL, managed database services)
- Knowledge of cloud migration strategies and hybrid cloud architectures
DevOps Engineer
AWS Infrastructure, CI/CD & Production Operations
Mumbai (On-site) | Full-time | 2-4 years
About the role:
Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a DevOps Engineer who will own day-to-day cloud infrastructure, deployment automation, and production operations across active customer engagements.
The mandatory requirement for this role is hands-on production experience on AWS, with infrastructure as code, container orchestration, and CI/CD pipelines owned end to end on at least one live customer workload. The role is hands-on. Expect to operate Kubernetes clusters, build CI/CD pipelines, automate environment provisioning, manage TLS and DNS, set up observability, and partner with backend and AI engineers to ship reliably. A typical week includes a Terraform refactor, a deployment pipeline build for a new service, an incident response on a production cluster, and a cost review.
Responsibilities:
- AWS infrastructure: Design and operate production infrastructure on AWS using EC2, EKS or ECS, S3, RDS, IAM, VPC, CloudFront, and Route53. Own configuration, networking, and cost.
- Infrastructure as code: Write and maintain Terraform or Pulumi modules. Drive consistency across environments and tenants through IaC rather than manual configuration.
- Kubernetes and containers: Operate production EKS clusters. Manage Helm charts, Ingress, autoscaling, secrets, and workload isolation.
- CI/CD pipelines: Build and maintain pipelines using GitHub Actions, GitLab CI, or equivalent. Include automated tests, security scans, and rollback paths.
- TLS, DNS, and CDN automation: Automate domain provisioning, TLS issuance (Let's Encrypt, cert-manager, ACM), and CDN configuration (CloudFront, Cloudflare).
- Observability and incident response: Set up monitoring, logging, and alerting using Prometheus, Grafana, ELK, Loki, or CloudWatch. Lead incident response and write postmortems.
- Secrets and security: Manage secrets through Vault, AWS Secrets Manager, or KMS. Apply least-privilege IAM and review access regularly.
- Cost monitoring: Track and optimise AWS spend across environments. Surface waste and propose remediations.
Requirements:
- Hands-on AWS production experience (mandatory). Must have personally operated production workloads on AWS, with responsibility for IaC, deployments, and incident response on at least one live customer or internal-platform deployment. POCs and lab environments do not qualify.
- 2 to 4 years of hands-on DevOps or infrastructure experience. Candidates with slightly less experience but strong demonstrated ownership are welcome to apply.
- AWS depth. Hands-on with EC2, S3, IAM, VPC, EKS or ECS, RDS, CloudFront, and Route53. Working knowledge of CloudWatch and AWS cost tooling.
- Kubernetes in production. Hands-on operation of EKS or equivalent. Comfort with Helm, Ingress controllers, autoscaling, and resource quotas.
- Infrastructure as code. Strong with Terraform (preferred) or Pulumi. Modular code, state management, and review discipline.
- CI/CD pipelines. Production experience with GitHub Actions, GitLab CI, or equivalent. Comfort with multi-environment pipelines and release strategies.
- Scripting and automation. Strong Bash and Python (or Go) for tooling. Linux fluency at the command line.
- Observability stack. Hands-on with Prometheus, Grafana, ELK or Loki, and at least one APM tool (Datadog, New Relic, or equivalent).
- Networking, TLS, and security fundamentals. Comfortable with DNS, TLS certificate lifecycle, VPC peering, and security groups.
Nice to have: multi-tenant SaaS infrastructure experience; service mesh (Istio, Linkerd); GitOps (ArgoCD, Flux); sandboxed execution environments (Firecracker, gVisor); exposure to platform engineering or developer-platform teams.
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.
Hiring for the below position with one of our premium client
Role: Senior DevOps Engineer
Exp:7+ years
Location: Chennai
Key skills: DevOps, Cloud, Python scripting
Description:
Strong analytical and problem-solving skills
Ability to work independently, learn quickly and be proactive
7-9 years overall and at least 3-4 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
If interested kindly apply!
We will share our workload as a team and we expect you to work on a broad range of tasks. Here’s are some of the things you might have to do on any given day:
- Developing APIs and endpoints for deployments of our product
- Infrastructure Development such as building databases, creating and maintaining automated jobs
- Build out the back-end to deploy and scale our product
- Build POCs for client deployments
- Document your code, write test cases, etc.
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)
Cloud native technologies - Kubernetes (EKS, GKE, AKS), AWS ECS, Helm, CircleCI, Harness, Severless platforms (AWS Fargate etc.)
Infrastructure as Code tools - Terraform, CloudFormation, Ansible
Scripting - Python, Bash
Desired Skills & Experience:
Projects/Internships with coding experience in either of Javascript, Python, Golang, Java etc.
Hands-on scripting and software development fluency in any programming language (Python, Go, Node, Ruby).
Basic understanding of Computer Science fundamentals - Networking, Web Architecture etc.
Infrastructure automation experience with knowledge of at least a few of these tools: Chef, Puppet, Ansible, CloudFormation, Terraform, Packer, Jenkins etc.
Bonus points if you have contributed to open source projects, participated in competitive coding platforms like Hackerearth, CodeForces, SPOJ etc.
You’re willing to learn various new technologies and concepts. The “cloud-native” field of software is evolving fast and you’ll need to quickly learn new technologies as required.
Communication: You like discussing a plan upfront, welcome collaboration, and are an excellent verbal and written communicator.
B.E/B.Tech/M.Tech or equivalent experience.
Role
We are looking for an experienced DevOps engineer that will help our team establish DevOps practice. You will work closely with the technical lead to identify and establish DevOps practices in the company.
You will also help us build scalable, efficient cloud infrastructure. You’ll implement monitoring for automated system health checks. Lastly, you’ll build our CI pipeline, and train and guide the team in DevOps practices.
This would be a hybrid role and the person would be expected to also do some application level programming in their downtime.
Responsibilities
- Deployment, automation, management, and maintenance of production systems.
- Ensuring availability, performance, security, and scalability of production systems.
- Evaluation of new technology alternatives and vendor products.
- System troubleshooting and problem resolution across various application domains and platforms.
- Providing recommendations for architecture and process improvements.
- Definition and deployment of systems for metrics, logging, and monitoring on AWS platform.
- Manage the establishment and configuration of SaaS infrastructure in an agile way by storing infrastructure as code and employing automated configuration management tools with a goal to be able to re-provision environments at any point in time.
- Be accountable for proper backup and disaster recovery procedures.
- Drive operational cost reductions through service optimizations and demand based auto scaling.
- Have on call responsibilities.
- Perform root cause analysis for production errors
- Uses open source technologies and tools to accomplish specific use cases encountered within the project.
- Uses coding languages or scripting methodologies to solve a problem with a custom workflow.
Requirements
- Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
- Prior experience as a software developer in a couple of high level programming languages.
- Extensive experience in any Javascript based framework since we will be deploying services to NodeJS on AWS Lambda (Serverless)
- Extensive experience with web servers such as Nginx/Apache
- Strong Linux system administration background.
- Ability to present and communicate the architecture in a visual form.
- Strong knowledge of AWS (e.g. IAM, EC2, VPC, ELB, ALB, Autoscaling, Lambda, NAT gateway, DynamoDB)
- Experience maintaining and deploying highly-available, fault-tolerant systems at scale (~ 1 Lakh users a day)
- A drive towards automating repetitive tasks (e.g. scripting via Bash, Python, Ruby, etc)
- Expertise with Git
- Experience implementing CI/CD (e.g. Jenkins, TravisCI)
- Strong experience with databases such as MySQL, NoSQL, Elasticsearch, Redis and/or Mongo.
- Stellar troubleshooting skills with the ability to spot issues before they become problems.
- Current with industry trends, IT ops and industry best practices, and able to identify the ones we should implement.
- Time and project management skills, with the capability to prioritize and multitask as needed.










