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Cloudelligent

<div>Position Title: Sr. AWS DevOps Engineer- Kubernetes Expertise 
Job Timings: 8am-5pm Central Time (US) 
Location: Islamabad
About Cloudelligent
Cloudelligent is Cloud-native consultancy and AWS Advanced consulting partner! We specialize in providing bespoke cloud solutions to the Startups, SMB &amp; enterprise segment. Being a next-gen cloud service provider, Cloudelligent helps businesses to make the most out of their cloud investment. We have an international footprint with a diverse team of domain experts, and we are customer obsessed.
Job Objective
As an experienced DevOps Engineer your primary role would be to build and deploy complex cloud environments for our customers using innovative automation tools and cutting-edge technologies. You will be responsible for setting up, maintaining, and evolving the AWS cloud architecture and supporting infrastructure monitoring and alerting, issues troubleshooting, and developing required automation for our customers.
Responsibilities<ul><li>
Work alongside a team of DevOps Engineers to architect, build, and deploy AWS cloud infrastructure that is redundant, resilient, scalable, self-sustaining, and self-healing.</li><li>
Promote infrastructure as code and automation as much as possible. To achieve this, you must have extensive knowledge of the DevOps tool sets like Terraform, Cloudformation, CircleCI, Gitlab, Jenkins, Docker, Kubernetes.</li><li>
Design, build, and maintain our Kubernetes infrastructure, including clusters, namespaces, and deployments.</li><li>
Work on projects independently with customers and stakeholders, gathering their requirements and informing them of new features and enhancements.</li><li>
Create and improve current operational practices and procedures.</li><li>
Ensure the implementation and maintenance of compliance and security practices in operational infrastructure.</li><li>
Responsible for training and mentoring junior DevOps engineers and new team members.</li></ul>
Requirements<ul><li>
Bachelor&rsquo;s in software/computer engineering, computer science or related field.</li><li>
Effective communication skills (proficiency in English language).</li><li>
5+ years of professional experience in DevOps engineering.</li><li>
4+ years of using CI/CD tools (Jenkins, CircleCI, Gitlab, or similar)</li><li>
Experience in Infrastructure as code (Terraform / Cloudformation/CDK) and using container orchestration tools (Kubernetes/EKS or ECS, Rancher, etc.)</li><li>
Experience of using configuration management tools (Puppet, Ansible, etc.) and working with containers (Docker or Docker-Compose, etc.)</li><li>
Experience of using Scripting when necessary (Bash, Python, Ruby, Go or Javascript, etc.)</li><li>
Self-driven, ability to work independently or as part of a project team with limited supervision.</li></ul>
Technical Experience/Expertise<ul><li>
Strong hands-on expertise with solution architecting environments in AWS cloud space.</li><li>
Strong hands-on experience with code pipeline design, development, and managing CI/CD workflows and tools.</li><li>
Comprehensive understanding and hands-on experience of core DevOps concepts (CI/CD, Agile &amp; Automation).</li><li>
Extensive experience in designing, deploying, and managing Kubernetes clusters in production environments.</li><li>
Expertise in containerization technologies such as Docker, including creating Docker images, managing Docker registries, and configuring Docker runtime environments.</li><li>
Familiarity with monitoring and logging tools such as Prometheus, Opentelemetry, Grafana, ELK stack (Elasticsearch, Logstash, Kibana).</li><li>
Extensive knowledge and hands-on experience of IP networking, VPN's, DNS, load balancing, and firewall.</li><li>
Extensive knowledge and hands-on experience with designing a secure infrastructure using current cloud-native security standards.</li></ul>
Good to have<ul><li>
AWS Certified Solutions Architect Associate/Professional and/or AWS Certified DevOps Professional</li><li>
Certified Kubernetes Administrator (CKA)</li></ul>
WLNJb5F0OR</div>

Sr. AWS DevOps Engineer- Kubernetes Expertise

Skylabs AI

<div>Skylabs AI is seeking a highly skilled Senior DevOps Engineer to join our innovative team dedicated to revolutionizing the AI landscape. As a key player in our organization, you will have the opportunity to streamline our development and operational processes, ensuring that our applications run smoothly and efficiently. This role is ideal for individuals who thrive in a fast-paced environment and are passionate about leveraging technology to enhance productivity. You will work closely with our development and IT teams to implement robust deployment pipelines, automate processes, and optimize system performance. Your expertise will play an essential role in improving collaboration across teams, enabling continuous integration and continuous delivery (CI/CD), and enhancing overall application reliability. At Skylabs AI, we believe in fostering a culture of continuous improvement and innovation, and we are eager to welcome a DevOps professional who shares our vision. Your contributions will directly impact our ability to deliver cutting-edge AI solutions to our clients while maintaining high levels of quality and efficiency. If you are ready to take on new challenges and make a significant impact in the world of AI and technology, we encourage you to apply.<h3 class="jobSectionHeader">
Responsibilities</h3><ul>
<li>Design and implement scalable CI/CD pipelines to streamline software delivery processes.</li>
<li>Monitor and optimize system performance, ensuring high availability and reliability of applications.</li>
<li>Collaborate with development teams to integrate automated testing and deployment practices into the workflow.</li>
<li>Manage cloud infrastructure and services, ensuring cost-effective and efficient resource allocation.</li>
<li>Implement security best practices throughout the DevOps process and infrastructure as code.</li>
<li>Troubleshoot and resolve complex infrastructure issues to minimize downtime and maintain service quality.</li>
<li>Provide training and support to development teams on best practices for CI/CD and infrastructure management.</li>
</ul>
Requirements<ul>
<li>
Bachelor's degree in Computer Science, Engineering, or related field.</li>
<li>Proven experience as a DevOps Engineer or similar role in software development and system administration.</li>
<li>Strong knowledge of CI/CD tools such as Jenkins, GitLab CI, or CircleCI.</li>
<li>Experience with cloud platforms such as AWS, Azure, or Google Cloud.</li>
<li>Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes.</li>
<li>Proficiency in scripting languages such as Python, Bash, or Ruby.</li>
<li>Solid understanding of networking, security, and server management principles.</li>
</ul>
Benefits<ul>
<li>
Competitive salary in USD
</li><li>Comprehensive health allowance
</li><li>Relocation allowance (if you're moving to Islamabad)
</li><li>Monthly team events and offsites
</li><li>A beautiful, collaborative office space</li>
<li>Work alongside world-class AI researchers and engineers</li></ul></div>

Senior DevOps Engineer

MicroAgility

<div>Roles and Responsibilities
<ul><li>Manage, monitor, and optimize Google Cloud Platform (GCP) infrastructure.</li><li>
Oversee application deployments on Google Kubernetes Engine (GKE) and ensure cluster performance.</li><li>
Perform cost optimization, scaling configuration, and resource planning across GCP services.</li><li>
Manage Identity and Access Management (IAM), service accounts, and security policies.</li><li>
Administer InMotion hosting infrastructure and maintain stable server performance.</li><li>
Oversee application deployments, updates, and maintenance on InMotion servers.</li><li>
Implement, test, and maintain backup and disaster recovery (DR) plans for InMotion Hosting &amp; GCP.</li><li>
Continuously monitor system performance and troubleshoot cloud, container, or configuration issues.</li><li>
Ensure secure and reliable integration between cloud and on-prem systems.</li><li>
Collaborate with cross-functional teams to design and improve cloud architecture.</li><li>
Provide technical guidance and enforce cloud best practices, security standards, and operational procedures.</li></ul>
Required Skills
<ul><li>Strong knowledge of Google Cloud Platform services and architecture.</li><li>
Hands-on experience with Kubernetes, GKE, Docker, and containerized deployments.</li><li>
Solid understanding of IAM, cloud security principles, and access control.</li><li>
Experience with Linux server administration and hosting platforms.</li><li>
Strong troubleshooting skills for cloud and orchestrated environments.</li><li>
Experience implementing backup strategies and disaster recovery procedures.</li><li>
Good communication skills and ability to work with technical and non-technical teams. 
 
Engagement Details 
</li><li>
Daily availability for 2 to 3 hours.</li><li>
Remote or hybrid support.</li><li>
Timely response and daily progress updates.</li></ul></div>

Cloud Consultant

<div><h3 class="jobSectionHeader">About Us</h3>
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.<h3 class="jobSectionHeader">
The Role</h3>
We are seeking an exceptional Senior Backend Engineer to lead the architecture and implementation of our entire cloud-native infrastructure. This is a foundational role responsible for building the scalable, resilient, and secure microservices platform that our AI agents and developer tools will run on.
You will be responsible for everything from our API gateways and database architecture to the Kubernetes-based remote execution sandboxes. You will design the asynchronous systems that manage long-running agentic tasks and build the high-throughput pipelines for LLM inference and telemetry. The ideal candidate is a &quot;10x&quot; backend expert who has built and scaled complex, AI-driven systems in production.
Requirements<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul>
<li>Microservice Architecture: Design, build, deploy, and maintain our platform as a set of resilient, scalable microservices (e.g., auth, payments, agent orchestration).</li>
<li>Agent Orchestration Backend: Build the critical systems that manage the lifecycle of long-running agentic tasks, including state management and asynchronous communication (Kafka, RabbitMQ, etc.).</li>
<li>Remote Sandboxing: Architect and implement the containerized execution environments (Docker, Kubernetes) where agents can safely build, test, and run code.</li>
<li>LLM Inference Infrastructure: Deploy, manage, and wrap high-throughput LLM inference servers (NVIDIA Triton, vLLM) to serve models to our agent systems.</li>
<li>API Design: Design, secure, and manage our core APIs (REST and gRPC), including our public-facing MCP/ACP and internal service-to-service communication.</li>
<li>Data &amp; Telemetry: Build the high-throughput data ingestion pipeline to process and store massive volumes of telemetry and training data from our IDE clients.</li>
<li>Identity &amp; Payments: Implement and manage our authentication (OAuth2/OIDC) and payment/subscription (Stripe) systems.</li>
<li>Infrastructure &amp; Observability: Own our Infrastructure as Code (Terraform) and build out comprehensive observability (Prometheus, Grafana, Jaeger) across the entire stack.</li>
</ul><h3 class="jobSectionHeader">Qualifications &amp; Skills</h3><h3 class="jobSectionHeader">
Core Profile: Sr. Backend Engineer</h3><ul>
<li>Expertise in Microservice Architectures: Proven ability to design, build, deploy, and maintain a complex system as a set of resilient, scalable, and independent microservices.</li>
<li>Advanced API Design &amp; Management: Mastery of designing clean, secure, and high-performance APIs (both REST and gRPC). Experience with API gateways, versioning, and documentation.</li>
<li>Database-agnostic Expertise: Deep practical experience with both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB, Redis) databases, including data modeling, query optimization, and scaling.</li>
<li>Scalable AI/LLM Infrastructure: Must have experience building and scaling backend systems specifically for LLM use cases, understanding the unique demands of stateful, long-running agentic tasks.</li>
<li>Comprehensive Observability: Experience building and managing full-stack observability (e.g., using Prometheus, Grafana, ELK/OpenSearch, and distributed tracing like Jaeger) to ensure system health and performance.</li>
<li>Authentication &amp; Authorization: Expertise in implementing robust identity systems, including sign-up, OAuth2/OIDC, JWTs, and fine-grained Role-Based Access Control (RBAC).</li>
<li>Payment Gateway Integration: Experience integrating and managing payment and subscription systems (e.g., Stripe), including metering and subscription logic.</li>
</ul><h3 class="jobSectionHeader">Specific Experience Required:</h3>
1. Agent Orchestration &amp; Remote Sandboxing<ul>
<li>
Agentic Mode Backend: This is critical. Experience designing systems that manage the lifecycle of complex, long-running &quot;agent&quot; tasks.</li>
<li>Containerized Execution: Deep experience with Docker and Kubernetes (K8s) for orchestrating the &quot;remote sandbox&quot; where agent-generated code is built, run, and tested securely. Familiarity with lightweight virtualization (e.g., Firecracker) is a major plus.</li>
<li>Asynchronous Task &amp; Message Queues: Expertise in using systems like Kafka, RabbitMQ, or gRPC streams to manage communication between microservices, the IDE plugin, and the AI agents, ensuring no data is lost.</li>
</ul>
2. LLM Model Hosting &amp; Inference<ul>
<li>
Model Hosting: Hands-on experience deploying and managing high-throughput LLM inference servers like NVIDIA Triton, TGI, or vLLM on GPU-enabled infrastructure.</li>
<li>Inference API Integration: Building the backend service that securely wraps these inference endpoints, handles request batching, and serves them to the agent orchestrator.</li>
</ul>
3. High-Throughput Data &amp; Cloud Infrastructure<ul>
<li>
Telemetry Ingestion: Designing and building a high-throughput data pipeline to receive, process, and store the massive volume of telemetry and training data sent from the IDE plugin.</li>
<li>Infrastructure as Code (IaC): Mastery of Terraform or CloudFormation to provision and manage the entire cloud infrastructure repeatedly and reliably.</li>
<li>API Security &amp; Management: Implementing rate limiting, request validation, and service-to-service authentication (e.g., mTLS) to protect the MCP/ACP and other public-facing endpoints.</li>
<li>CI/CD &amp; DevOps: A strong DevOps mindset and experience building automated CI/CD pipelines (e.g., GitLab CI, GitHub Actions) for a microservices environment.</li>
</ul><h3 class="jobSectionHeader">Who You Are</h3>
You are a builder at heart, driven by curiosity and a desire to solve hard problems. You don't wait for instructions; you identify opportunities and seize them. You are comfortable with ambiguity and thrive in a fast-paced, in-depth environment where you are encouraged to experiment and push boundaries. You are a clear communicator who can articulate complex technical concepts and work collaboratively to achieve ambitious goals.
Benefits<h3 class="jobSectionHeader">
What We Offer</h3><ul>
<li>Competitive salary in USD</li>
<li>Comprehensive health allowance</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Monthly team events and offsites</li>
<li>A beautiful, collaborative office space</li>
<li>Work alongside world-class AI researchers and engineers</li></ul></div>

Senior Backend Engineer

SkyLabs AI

<div>
 
 About Us
 
 
 
 At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
 
 
 
 The Role
 
 
 
 We are seeking an exceptional Senior Backend Engineer to lead the architecture and implementation of our entire cloud-native infrastructure. This is a foundational role responsible for building the scalable, resilient, and secure microservices platform that our AI agents and developer tools will run on.
 
 
 You will be responsible for everything from our API gateways and database architecture to the Kubernetes-based remote execution sandboxes. You will design the asynchronous systems that manage long-running agentic tasks and build the high-throughput pipelines for LLM inference and telemetry. The ideal candidate is a "10x" backend expert who has built and scaled complex, AI-driven systems in production.
 
 
 
 Requirements
 
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Microservice Architecture: Design, build, deploy, and maintain our platform as a set of resilient, scalable microservices (e.g., auth, payments, agent orchestration)
 </li>
 <li>
 Agent Orchestration Backend: Build the critical systems that manage the lifecycle of long-running agentic tasks, including state management and asynchronous communication (Kafka, RabbitMQ, etc.)
 </li>
 <li>
 Remote Sandboxing: Architect and implement the containerized execution environments (Docker, Kubernetes) where agents can safely build, test, and run code
 </li>
 <li>
 LLM Inference Infrastructure: Deploy, manage, and wrap high-throughput LLM inference servers (NVIDIA Triton, vLLM) to serve models to our agent systems
 </li>
 <li>
 API Design: Design, secure, and manage our core APIs (REST and gRPC), including our public-facing MCP/ACP and internal service-to-service communication
 </li>
 <li>
 Data &amp; Telemetry: Build the high-throughput data ingestion pipeline to process and store massive volumes of telemetry and training data from our IDE clients
 </li>
 <li>
 Identity &amp; Payments: Implement and manage our authentication (OAuth2/OIDC) and payment/subscription (Stripe) systems
 </li>
 <li>
 Infrastructure &amp; Observability: Own our Infrastructure as Code (Terraform) and build out comprehensive observability (Prometheus, Grafana, Jaeger) across the entire stack
 
 
 </li>
 </ul>
 
 Qualifications &amp; Skills
 
 
 
 
 Core Profile: Sr. Backend Engineer
 
 
 
 <ul>
 <li>
 Expertise in Microservice Architectures: Proven ability to design, build, deploy, and maintain a complex system as a set of resilient, scalable, and independent microservices
 </li>
 <li>
 Advanced API Design &amp; Management: Mastery of designing clean, secure, and high-performance APIs (both REST and gRPC). Experience with API gateways, versioning, and documentation
 </li>
 <li>
 Database-agnostic Expertise: Deep practical experience with both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB, Redis) databases, including data modeling, query optimization, and scaling
 </li>
 <li>
 Scalable AI/LLM Infrastructure: Must have experience building and scaling backend systems specifically for LLM use cases, understanding the unique demands of stateful, long-running agentic tasks
 </li>
 <li>
 Comprehensive Observability: Experience building and managing full-stack observability (e.g., using Prometheus, Grafana, ELK/OpenSearch, and distributed tracing like Jaeger) to ensure system health and performance
 </li>
 <li>
 Authentication &amp; Authorization: Expertise in implementing robust identity systems, including sign-up, OAuth2/OIDC, JWTs, and fine-grained Role-Based Access Control (RBAC)
 </li>
 <li>
 Payment Gateway Integration: Experience integrating and managing payment and subscription systems (e.g., Stripe), including metering and subscription logic
 
 
 </li>
 </ul>
 
 Specific Experience Required:
 
 
 Who You Are
 
 
 
 <ul>
 <li>
 Agent Orchestration &amp; Remote Sandboxing
 </li>
 <li>
 Agentic Mode Backend: This is critical. Experience designing systems that manage the lifecycle of complex, long-running "agent" tasks
 </li>
 <li>
 Containerized Execution: Deep experience with Docker and Kubernetes (K8s) for orchestrating the "remote sandbox" where agent-generated code is built, run, and tested securely. Familiarity with lightweight virtualization (e.g., Firecracker) is a major plus
 </li>
 <li>
 Asynchronous Task &amp; Message Queues: Expertise in using systems like Kafka, RabbitMQ, or gRPC streams to manage communication between microservices, the IDE plugin, and the AI agents, ensuring no data is lost
 </li>
 <li>
 LLM Model Hosting &amp; Inference
 </li>
 <li>
 Model Hosting: Hands-on experience deploying and managing high-throughput LLM inference servers like NVIDIA Triton, TGI, or vLLM on GPU-enabled infrastructure
 </li>
 <li>
 Inference API Integration: Building the backend service that securely wraps these inference endpoints, handles request batching, and serves them to the agent orchestrator
 </li>
 <li>
 High-Throughput Data &amp; Cloud Infrastructure
 </li>
 <li>
 Telemetry Ingestion: Designing and building a high-throughput data pipeline to receive, process, and store the massive volume of telemetry and training data sent from the IDE plugin
 </li>
 <li>
 Infrastructure as Code (IaC): Mastery of Terraform or CloudFormation to provision and manage the entire cloud infrastructure repeatedly and reliably
 </li>
 <li>
 API Security &amp; Management: Implementing rate limiting, request validation, and service-to-service authentication (e.g., mTLS) to protect the MCP/ACP and other public-facing endpoints
 </li>
 <li>
 CI/CD &amp; DevOps: A strong DevOps mindset and experience building automated CI/CD pipelines (e.g., GitLab CI, GitHub Actions) for a microservices environment
 
 
 </li>
 </ul>
 You are a builder at heart, driven by curiosity and a desire to solve hard problems. You don't wait for instructions; you identify opportunities and seize them. You are comfortable with ambiguity and thrive in a fast-paced, in-depth environment where you are encouraged to experiment and push boundaries. You are a clear communicator who can articulate complex technical concepts and work collaboratively to achieve ambitious goals.
 
 
 
 Benefits
 
 
 
 
 What We Offer
 
 
 
 <ul>
 <li>
 Competitive salary in USD
 </li>
 <li>
 Comprehensive health allowance
 </li>
 <li>
 Relocation allowance (if you're moving to Islamabad)
 </li>
 <li>
 Monthly team events and offsites
 </li>
 <li>
 A beautiful, collaborative office space
 </li>
 <li>
 Work alongside world-class AI researchers and engineers
 </li>
 </ul>
</div>

XTIUM

<div>
 
 The XTIUM global team is made up of a group of diverse and talented professionals who are all driven by the same goal: excellence and continuous improvement. We are all about embracing challenges, keeping the lines of communication open and working together. We take ownership of our work, focus on learning and growing and hold ourselves accountable to our colleagues and customers. Together, we strive to push boundaries, make an impact and inspire each other to reach our full potential.
 
 
 
 
 Job Description
 
 
 
 JOB RESPONSIBILITIES
 
 
 <ul>
 <li>
 Design, deploy, and manage cloud infrastructure using AWS best practices.
 </li>
 <li>
 Monitor, troubleshoot, and optimize performance in production environments.
 </li>
 <li>
 Ensure system security, data protection, and compliance with organizational and regulatory standards.
 </li>
 <li>
 Support high availability and disaster recovery planning and implementation.
 </li>
 <li>
 Collaborate with developers and other engineers to support application deployment and scalability.
 </li>
 <li>
 Respond to production incidents and participate in root cause analysis and remediation.
 </li>
 <li>
 Provision, configure, and manage cloud resources including EC2/VMs, storage, security groups, load balancers, VPC networking, IAM policies.
 </li>
 <li>
 Support hybrid environments and assist customers with migrations between on-prem and cloud.
 </li>
 <li>
 Monitor infrastructure performance and availability using CloudWatch, Azure Monitor, and other alerting tools.
 </li>
 <li>
 Respond to support tickets for outages, degraded performance, networking issues, and account configuration requests.
 </li>
 <li>
 Implement cloud security controls, patching oversight, backup and recovery operations.
 </li>
 <li>
 Troubleshoot connectivity, DNS, VPN, firewall/security rule issues across AWS and Azure.
 </li>
 <li>
 Assist with tagging, reporting, and resource governance to ensure compliance and cost optimization.
 </li>
 <li>
 Participate in on-call rotations and incident root-cause reviews.
 </li>
 <li>
 Partner with internal teams and the customer on improving operational reliability.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 AWS Certification required (SysOps Administrator preferred; Solutions Architect or similar acceptable).
 </li>
 <li>
 3&ndash;5+ years in AWS cloud operations or support engineering roles (Azure experience strongly preferred as secondary skill).
 </li>
 <li>
 Strong understanding of:
 </li>
 <li>
 VPC networking, transit gateways, routing, subnets, security groups, NACLs
 </li>
 <li>
 EC2 sizing, EBS, snapshots, load balancers, Availability Zones, IAM
 </li>
 <li>
 Hands-on experience supporting production systems and responding to incidents.
 </li>
 <li>
 Experience with ticketing workflows and service delivery (ITIL familiarity is a plus).
 </li>
 <li>
 Scripting for automation (PowerShell, Bash, or Python) &mdash; light usage; not a developer role.
 </li>
 <li>
 Familiarity with Azure equivalent services (VMs, VNets, NSGs, AAD, monitoring, Storage Accounts).
 
 
 </li>
 </ul>
 
 Job Requirements
 
 
 
 <ul>
 <li>
 Should be willing to accept a long-term work-from-home arrangement.
 </li>
 <li>
 Should be amenable to a permanent night shift schedule.
 
 
 </li>
 </ul>
 Remote
</div>

AWS Cloud Engineer

Datamatics Global Services Ltd

<div><h3 class="jobSectionHeader">Job Title: DevOps / MLOps Engineer</h3>
Experience: 7&ndash;9 Years 
Location: Remote<h4 class="jobSectionHeader"> 
Job Summary</h4>
We are seeking a skilled DevOps Engineer with hands-on MLOps experience to design, automate, and manage scalable infrastructure and CI/CD pipelines for cloud-native and machine learning workloads. The role requires strong expertise in automation, container orchestration, and continuous delivery, with a focus on reliability, performance, and scalability.<h4 class="jobSectionHeader"> 
Key Responsibilities</h4><ul><li>
Design, build, and maintain CI/CD pipelines using Jenkins and automation tools</li><li>
Implement and manage MLOps pipelines for model training, deployment, monitoring, and retraining</li><li>
Deploy, manage, and scale containerized applications using Kubernetes</li><li>
Automate infrastructure provisioning and configuration using IaC tools</li><li>
Manage cloud infrastructure and services on Google Cloud Platform (GCP)</li><li>
Ensure high availability, security, and performance of platforms and pipelines</li><li>
Collaborate with data scientists and engineers to productionize ML models</li><li>
Monitor systems, optimize costs, and troubleshoot production issues</li></ul><h4 class="jobSectionHeader"> 
Required Skills &amp; Experience</h4><ul><li>
Strong experience as a DevOps Engineer with exposure to MLOps practices</li><li>
Hands-on expertise with Kubernetes (deployment, scaling, networking)</li><li>
Strong experience with Jenkins for CI/CD automation</li><li>
Experience with automation and scripting tools (Terraform, Ansible, Bash, Python, etc.)</li><li>
Strong understanding of containerization (Docker) and microservices architecture</li><li>
Experience with monitoring, logging, and alerting solutions</li></ul><h4 class="jobSectionHeader"> 
Nice to Have</h4><ul><li>
Experience with ML platforms such as Kubeflow, Vertex AI, or MLflow</li><li>
Knowledge of GitOps tools (ArgoCD, Flux)</li><li>
Experience with security, IAM, and compliance in cloud environments</li></ul>
YR6JMI01Y8</div>

DevOps / MLOps Engineer

Explore 184+ Cloud infrastructure engineer in Islamabad this January. Find roles across top companies and apply now to boost your career.

184 cloud infrastructure engineer jobs IN Islamabad

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DevOps / MLOps Engineer