dev ops engineer

Mastercard

<div><p><b>Our Purpose</b></p><p></p><p><i>
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.</i></p><p></p><p><b>
Title and Summary</b></p><p></p>
BizOps Engineer II<p></p>
The RTP International BizOps team is looking for a BizOps Engineer who can help us solve problems, build our CI/CD pipeline and lead Mastercard in DevOps automation and best practices.<br>
<br>
<ul><li>Are you a born problem solver who loves to figure out how something works?</li><li>Are you a CI/CD geek who loves all things automation?</li><li>Do you have a low tolerance for manual work and look to automate everything you can?</li></ul><br>
Business Operations is leading the DevOps transformation at Mastercard through our tooling and by being an advocate for change &amp; standards throughout the development, quality, release, and product organizations. We need team members with an appetite for change and pushing the boundaries of what can be done with automation. Experience in working across development, operations, and product teams to prioritize needs and to build relationships is a must.<br>
<br>
Role<br>
<br>
The role of business operations is to be the production readiness steward for the platform. This is accomplished by closely partnering with developers to design, build, implement, and support technology services.<br>
<br>
A business operations engineer will ensure operational criteria like system availability, capacity, performance, monitoring, self-healing, and deployment automation are implemented throughout the delivery process. Business Operations plays a key role in leading the DevOps transformation at Mastercard through our tooling and by being an advocate for change and standards throughout the development, quality, release, and product organisations.<br>
<br>
We accomplish this transformation through supporting daily operations with a hyper-focus on triage and then root cause by understanding the business impact of our products. The goal of every biz ops team is to shift left to be more proactive and upfront in the development process and to proactively manage production and change activities to maximize customer experience and increase the overall value of supported applications.<br>
<br>
Biz Ops teams also focus on risk management by tying all our activities together with an overarching responsibility for compliance and risk mitigation across all our environments. A biz ops focus is also on streamlining and standardizing traditional application specific support activities and centralizing points of interaction for both internal and external partners by communicating effectively with all key stakeholders.
<br>
<br>
Ultimately, the role of biz ops is to align Product and Customer Focused priorities with Operational needs. We regularly review our run state not only from an internal perspective but also understanding and providing the feedback loop to our development partners on how we can improve the customer experience of our applications.<br>
<br>
Role<br>
<br>
<ul><li>Engage in and improve the whole lifecycle of services&mdash;from inception and design, through deployment, operation and refinement.</li><li>Analyze ITSM activities of the platform and provide a feedback loop to development teams on operational gaps or resiliency concerns</li><li>Maintain services once they are live by measuring and monitoring availability, latency and overall system health.</li><li>Practice sustainable incident response and blameless postmortems.</li><li>Take a holistic approach to problem-solving, by connecting the dots during a production event through the various technology stack that makes up the platform, to optimize mean time to recover</li><li>Work with a global team spread across tech hubs in multiple geographies and time zones</li><li>Share knowledge and mentor junior resources</li></ul><br>
For team members supporting the Application through monitoring:<br>
<ul><li>Partner with our BizOps teams globally to deliver against our incident response commitments.</li><li>Champion our efforts to push forward with smarter, more adaptable monitoring and alerting tools to support our products globally.</li><li>Take an active role in the review of process and procedures to better serve the team and our product.</li></ul><p></p><p><b>
Corporate Security Responsibility</b></p><p><br>
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:</p><ul><li><p>
Abide by Mastercard&rsquo;s security policies and practices;</p></li><li><p>
Ensure the confidentiality and integrity of the information being accessed;</p></li><li><p>
Report any suspected information security violation or breach, and</p></li><li><p>
Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.</p></li></ul></div><p></p>

BizOps Engineer II

Luxoft

<div><div><h5 class="jobSectionHeader"><b>Project description
</b></h5><p>We are hiring an ML Ops Engineer to operationalize machine learning solutions across Digital Oilfield (DOF) platforms. This is a critical role ensuring that models move from development to robust, production-grade deployment with high availability, traceability, and security.<br>
The ideal candidate will be responsible for automating pipelines, managing model versions, integrating APIs, and monitoring ML system health across diverse operational environments. Oil &amp; gas exposure is beneficial but not required; this is a technical engineering role with high ownership and cross-team collaboration.
</p></div><div><h5 class="jobSectionHeader"><b>Responsibilities</b></h5>
<div><div><p>Develop and maintain ML pipelines for data preprocessing, training, validation, deployment, and monitoring.
</p></div><div><p>Implement model governance strategies&mdash;versioning, rollback, audit trails, and explainability.
</p></div><div><p>Set up containerized environments and scalable inference systems (e.g., using Docker, Kubernetes).
</p></div><div><p>Collaborate with software, IT, and data teams to ensure model integration and compliance.
</p></div><div><p>Support continuous improvement of ML lifecycle management practices and tooling.
</p></div><div><p>Business trip to Kuwait for first 6-12 months. On-site
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Skills</b></h5>
<p>Must have
</p><div><div><p>Strong software engineering background with ML Ops or DevOps exposure
</p></div><div><p>Hands-on experience with MLflow, Azure ML, Kubeflow, or equivalent.
</p></div><div><p>Proficiency in CI/CD workflows and scripting for automation.
</p></div><div><p>Familiarity with model monitoring, drift detection, and alerting frameworks.
</p></div><div><p>Experience deploying Python-based ML models in production.
</p></div><div><p>Ready for a long term business trip to Kuwait for first 6-12 months
</p></div></div><p>Nice to have
</p><div><div><p>Understanding of Digital Oilfield environments or OT/IT integration.
</p></div><div><p>Familiarity with cloud-native services&mdash;Azure is preferred.
</p></div><div><p>Exposure to real-time data streaming (e.g., Kafka, IoT platforms).
</p></div><div><p>Understanding of security, compliance, and data access protocols in enterprise environments.
</p></div><div><p>Certifications:
</p></div><div><p>Azure DevOps or Azure AI Engineer certification is a plus.
</p></div><div><p>AWS DevOps Engineer certification is nice to have but not required
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Other</b></h5>
<div><div><div><p>Languages</p>
<p>English: C1 Advanced
</p></div></div><div><div><p>Seniority</p>
<p>Senior</p></div></div></div></div></div>
<br><div><div><div><p>Remote Egypt, Egypt
</p></div><p>Req. VR-118737
</p></div><div></div><div><div><p>DevOps
</p></div><div><p>Cross Industry Solutions</p>
</div><div><p>20/02/2026
</p></div><div><p>Req. VR-118737</p></div></div></div><p></p>

ML Ops Engineer (onsite work in Kuwait)

Michelin

<div>Machine Learning Ops Engineer<div>
- - - - - - - - - - - -</div><div>
Machine Learning Ops Engineer is the one who&rsquo;s responsible for managing and optimizing the deployment and operation of machine learning models in production environments. He/she works closely with data scientists, software engineers, and DevOps teams to ensure that machine learning models are integrated seamlessly into existing systems and can scale effectively.</div><div>
Role &amp; Responsibilities &ndash;<br>
➢ Responsible for design and implementation of secure and scalable infrastructure in Azure cloud.<br>
➢ Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects.<br>
➢ Own and automate the infrastructure provisioning, demand forecasting and capacity planning.<br>
➢ Build tools and automation to improve systems availability, reliability, performance, monitoring and scalability.<br>
➢ Setting up the alerts and monitoring for the platform.<br>
➢ Monitoring system, application health, security controls and cost<br>
➢ Envision, implement and rollout best MLOPs/DevOps tools and automation.</div><div></div><div>
Requirements:</div><div>
➢ Strong understanding of concepts related to Machine Learning, Architecture, and MLOps practices.</div><div>
➢ Proficient in Azure Cloud practices and managing Azure Kubernetes Service infrastructure.</div><div>
➢ Hands on experience in Python or any other scripting languages (Groovy, Shell)</div><div>
➢ Experience with monitoring tools.</div><div>
➢ Hands-on experience in Docker, Kubernetes.</div><div>
➢ Excellent experience with source code management tools (git)</div><div>
➢ Experience with modern cloud development practices such as Microservices Architecture, REST Interfaces etc.</div><div>
➢ Experience in implementing Data/Model drift.</div><div>
➢ Strive for Continuous Improvement and build continuous integration, continuous development, and constant deployment pipeline.</div><div>
➢ Excellent Troubleshooting skills</div><div>
➢ Always ready to learn more and adopt new cutting-edge technology with right value proposition.</div></div>

Machine Learning Ops Engineer

PROZ TECHNOLOGIES

<p>Job Description:</p><p>The DevOps Engineer will design, implement, and maintain modern cloud-native infrastructure and continuous integration/continuous delivery (CI/CD) pipelines across enterprise and industrial digital platforms. This role combines software engineering, system administration, automation, and operations to deliver high-performing, scalable, and secure infrastructure supporting the organization&rsquo;s data and AI initiatives.</p><p>The engineer will collaborate closely with data engineers, software developers, cloud architects, and cybersecurity teams to ensure consistent, automated, and compliant cloud deployments within a multi-cloud (Azure and GCP) environment.</p><p>Key Responsibilities:</p><p>Cloud Infrastructure &amp; Automation</p><ul><li>Design, build, and manage cloud infrastructure (Azure and GCP) using Infrastructure-as-Code (IaC) tools such as Terraform, ARM templates, and Ansible.</li><li>Automate provisioning, scaling, and configuration of compute, storage, and networking resources.</li><li>Implement and maintain container orchestration platforms such as Kubernetes, OpenShift, and Docker Swarmfor scalable deployments.</li><li>Develop and maintain GitOps workflows using Azure DevOps, GitHub Actions, or Jenkins for automated CI/CD processes.</li><li>Integrate infrastructure automation with Microsoft Graph, REST APIs, and ServiceNow for operational efficiency.</li></ul><p>CI/CD Pipeline Development</p><ul><li>Design and manage end-to-end CI/CD pipelines for application, data, and AI workloads.</li><li>Automate build, test, and deployment processes across environments (Dev, Test, Prod).</li><li>Integrate pipelines with code scanning, static analysis, and container security tools (e.g., Snyk, Aqua, Prisma Cloud).</li><li>Implement blue-green and canary deployments to ensure zero-downtime releases.</li></ul><p>Monitoring, Observability &amp; Reliability</p><ul><li>Implement comprehensive monitoring, logging, and alerting using Azure Monitor, Log Analytics, Prometheus, Grafana, and ELK Stack.</li><li>Develop automated alerts and dashboards for real-time performance, resource utilization, and cost monitoring.</li><li>Participate in incident response, root cause analysis, and performance optimization of infrastructure and pipelines</li></ul><p>Security, Compliance &amp; Governance</p><ul><li>Work closely with the cybersecurity team to integrate security-as-code and compliance controls within DevOps workflows.</li><li>Manage secrets, keys, and credentials using Azure Key Vault, and HashiCorp Vault.</li><li>Ensure compliance with ISO 27001, NIA Qatar, CIS Benchmarks, and corporate governance standards.</li><li>Implement network security controls (NSGs, firewalls, WAFs, VNETs) and enforce Zero Trust principles across CI/CD deployments.</li><li>Collaboration &amp; Continuous Improvement</li><li>Partner with Data Science and AI teams to operationalize model training and deployment pipelines (MLOps).</li><li>Collaborate with development teams to containerize and deploy cloud-native applications.</li><li>Identify and implement process improvements to enhance release velocity and reduce deployment risk.</li><li>Stay abreast of emerging technologies and DevOps trends to continuously evolve automation maturity.</li></ul><p><b>Required Skills and Qualifications:</b></p><ul><li>Bachelor's degree in computer science, Engineering, or related field (or equivalent professional experience).</li><li>10+ years of experience as a DevOps Engineer or Cloud Infrastructure Engineer in enterprise or industrial environments.</li><li>Proven expertise in CI/CD pipelines, automation, and cloud-based infrastructure.</li><li>Strong hands-on experience with at least one major cloud provider.</li><li>Infrastructure as Code: Terraform, Ansible, ARM Templates, CloudFormation.</li><li>CI/CD Tools: Azure DevOps, Jenkins, GitHub Actions, GitLab CI.</li><li>Containers &amp; Orchestration: Docker, Kubernetes, OpenShift.</li><li>Scripting &amp; Programming: Python, PowerShell, Bash, YAML.</li><li>Monitoring &amp; Observability: Azure Monitor, Log Analytics, Prometheus, Grafana, ELK Stack.</li><li>Version Control &amp; Collaboration: Git, GitHub, Azure Repos, Bitbucket.</li><li>Cloud Services Knowledge:</li><li>Compute (VMs, Functions, App Services)</li><li>Storage (Blob, S3, GCS)</li><li>Networking (VPCs/VNets, Load Balancers, VPNs, ExpressRoute)</li><li>Security (Key Vault, IAM, Defender for Cloud)</li><li>Good understanding of networking principles, cloud security, load balancing, and microservices architecture.</li><li>Experience in automation of monitoring, scaling, and deployments across hybrid cloud environments.</li></ul><p>Job Types: Full-time, Permanent, Contract<br/>Contract length: 12 months</p><p>Pay: Up to QAR20,000.00 per month</p><p>Work Location: In person</p>

DevOps Engineer

NVIDIA

<div><div>NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It&rsquo;s a unique legacy of innovation that&rsquo;s fueled by great technology&mdash;and amazing people. Today, we&rsquo;re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what&rsquo;s never been done before takes vision, innovation, and the world&rsquo;s best talent. As an NVIDIAN, you&rsquo;ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.</div><div></div><div>
Join our team of innovative engineers who are building an AI Data Center AIOps platform that turns raw, high-volume telemetry into reliable, job-centric insights and automation for GPU fleets. We&rsquo;re hiring a DevOps Engineer to operate the platform itself (not the compute cluster): uptime, performance, data integrity, and safe change management. You&rsquo;ll own SLOs/SLIs, incident response, and postmortems for the telemetry ingestion, processing, storage, and APIs/dashboards that operators depend on. You&rsquo;ll partner Software Engineering and Systems Engineering team to translate platform signals into actionable, trustworthy alerts and automation.</div><div></div><div>
What you'll be doing:</div><ul><li><div>
Continuously monitor platform health via dashboards/logs/metrics, automate recurring checks, and keep reliability + resource efficiency on track.</div></li><li><div>
Own Kubernetes deployments end-to-end (runbooks, canary checks, post-deploy validation), and lead rollbacks/remediations when needed.</div></li><li><div>
Lead first-level incident triage: collect diagnostics, identify likely root causes, and hand off clear, actionable findings to engineering.</div></li><li><div>
Build and maintain runbooks/SOPs/checklists, pushing continuous improvement through automation.</div></li><li><div>
Manage deployment infrastructure and packaging (Helm + Terraform/IaC) to keep environments scalable, consistent, and reproducible.</div></li><li><div>
Contribute in adjacent functional areas to grow and help your team members!</div></li></ul><div></div><div>
What we need to see:</div><ul><li><div>
BS/MS in CS/CE (or equivalent experience) and 5+ years operating production distributed systems as SRE/DevOps/Platform Ops.</div></li><li><div>
Proven ownership of reliability for an observability/AIOps platform: SLOs/SLIs, on-call, addressing incidents, and follow-up evaluations that drive measurable improvements.</div></li><li><div>
Deep Kubernetes + containers experience (deploying, debugging, scaling) for telemetry-heavy microservices&mdash;ingestion, processing, storage, APIs, and UI.</div></li><li><div>
Automation-first approach: solid scripting (Python/Bash), CI/CD, and infrastructure-as-code (Terraform + Helm) to deliver safe rollouts (canaries/rollbacks), reproducible environments, and minimal toil.</div></li><li><div>
Clear communicator who writes excellent runbooks/docs and can translate ambiguous requirements into concrete operational practices and dependable customer-facing reliability.</div></li></ul><div></div><div>
Ways to stand out from the crowd:</div><ul><li><div>
Strong Linux + networking fundamentals, distributed systems instincts, and hands-on ops for Kubernetes/services/streaming stacks are ideal; bonus for experience with observability platforms at scale.</div></li><li><div>
Experience building safe automation that operators trust: canary releases, automated rollback criteria, &ldquo;monitoring for the monitoring&rdquo; (lag/drop/error budgets), and replay/backfill pipelines with correctness checks.</div></li><li><div>
Strong in distributed/streaming systems operations (Kafka/Pulsar, Flink/Spark, ClickHouse/Elastic/TSDBs, object storage)&mdash;and can reason about backpressure, hotspots, and failure domains end-to-end.</div></li><li><div>
Proven programming experience building automation tools or services &mdash; ideally in Python, or similar languages &mdash; to simplify operations and scale recurring processes.</div></li><li><div>
Proven experience running large‑scale production deployments and multiple Kubernetes environments or clusters across teams or customers, coordinating changes and rollouts with minimal disruption with hands‑on experience with observability tools &mdash; you know your way around dashboards, metrics, logs, and traces using platforms like Prometheus, Grafana, or similar.</div></li></ul><div></div><div>
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.</div><div></div>
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 176,000 USD - 276,000 USD for Level 4.<div></div><div><div><div><div><div><div><div><div>
You will also be eligible for equity and <div>benefits</div>.</div></div></div></div></div></div></div></div><div></div>
Applications for this job will be accepted at least until February 27, 2026.<div></div><div>
This posting is for an existing vacancy.</div><div>
NVIDIA uses AI tools in its recruiting processes.</div><div></div>
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.</div><div></div>

Senior DevOps Engineer, AIOPs

Deeplight

<p></p><div><p>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.</p><p>
The ML Ops and DevOps Engineer is a specialised technical role focused on bridging the gap between AI development and production-grade operations. You will design, deploy, and manage scalable AI solutions primarily across AWS and Azure environments, integrating Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps). By leveraging containerization, automated CI/CD pipelines, and robust data engineering, you will ensure that the Bank&rsquo;s AI-driven applications&mdash;including Generative AI and LLM agents&mdash;are secure, efficient, compliant, and highly available.</p><p></p><p>
Your responsibilities as the MLOps and DevOps Engineer include:</p><ul>
<li>
Design and deploy scalable AI infrastructure using GitHub Actions, EKS, ECS, and AWS Lambda; automate all resource provisioning via Terraform.</li>
<li>Create and manage end-to-end CI/CD pipelines for model deployment, versioning, and lifecycle management using Azure DevOps and GitHub Actions.</li>
<li>Deploy machine learning and large language models via Amazon SageMaker, EKS, and Azure ML Endpoints.</li>
<li>Implement comprehensive monitoring for model performance and drift using Amazon CloudWatch, SageMaker Model Monitor, and OpenSearch.</li>
<li>Integrate advanced services including Azure OpenAI, Azure Cognitive Services, and AWS Rekognition into enterprise workflows.</li>
<li>Design robust data pipelines and real-time ingestion streams using AWS Glue, Amazon Redshift, Athena, and Apache Spark.</li>
<li>Enforce cloud security through AWS WAF, Azure Key Vault, and RBAC, ensuring all deployments meet GDPR and ISO compliance standards.</li>
<li>Supervise team activities and contribute to change initiatives in line with the Bank&rsquo;s continuous improvement standards.</li>
</ul><p></p><p><i>
As an AI consultancy, our greatest asset is the expertise of our people.<br>
</i></p><p><br>
<i>While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.<br>
</i></p><p><br>
<i>We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.<br>
</i></p><p><br>
<i>You will be the face of our firm, tasked with building trust, articulating the &quot;why&quot; behind your technical decisions, and effectively &quot;selling&quot; your vision to high-level stakeholders.<br>
</i></p><p><br>
<i>If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.</i></p><p><b>
Requirements</b></p><p>
What we need from you:</p><p></p><ul>
<li>
A Bachelor&rsquo;s degree in Computer Science, AI, Software Engineering, Statistics, Mathematics, or a related quantitative field.</li>
<li>A minimum of 5 years in designing and deploying AI solutions in cloud environments, specifically within MLOps/LLMOps frameworks.</li>
<li>Proficiency with GitHub Actions, Spark, Redshift, MongoDB, and Azure Purview.</li>
<li>Deep hands-on expertise in AWS (SageMaker, EKS, S3) and Azure (OpenAI, Cognitive Services) ecosystems.</li>
<li>Mastery of Terraform for multi-cloud resource automation.</li>
<li>Proven experience in both MLOps (standard ML) and LLMOps (Large Language Models), focusing on fine-tuning, orchestration, and monitoring.</li>
<li>Expertise in managing container images via ECR/ACR and deploying via Kubernetes (EKS/AKS).</li>
<li>Strong understanding of secure networking (WAF, NSGs) and secret management.</li>
</ul><p></p><p>
It would be beneficial if you also have:</p><br>
<ul>
<li>
Azure and/or AWS certifications (e.g., AWS Certified Machine Learning - Specialty or Azure AI Engineer Associate) are highly preferred.</li>
<li>Ability to seamlessly manage workloads that span across both AWS and Azure.</li>
<li>Skill in communicating complex technical infrastructure requirements to non-technical business stakeholders.</li>
<li>Adaptability in troubleshooting model drift and performance bottlenecks in real-time agentic workflows.</li>
<li>Proactive identification of new tools (e.g., Vector DBs, orchestration frameworks) to improve deployment velocity.</li>
</ul><p><b>
Benefits</b></p><p><b>
Benefits &amp; Growth Opportunities:</b></p><ul>
<li>
Competitive salary.</li>
<li>Visa Sponsorship for the successful individual.
</li><li>Comprehensive health insurance for the successful individual.
</li><li>Professional development and certification support.</li>
<li>Opportunity to work on cutting-edge AI projects.</li>
<li>Career advancement opportunities in a rapidly growing AI company.</li>
</ul><p></p><p>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.</p><p>
At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.</p><p>
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.</p><p>
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.</p></div><p></p>

ML Ops and DevOps Engineer

M2A Facility Management GmbH

<p>Senior DevOps Engineer</p><p>About the Role</p><p>We are looking for a <b>Senior DevOps Engineer</b> with deep experience in cloud technologies and a strong background in modern web architectures. The ideal candidate is passionate about <b>automation, scalability, and security</b>, with hands-on experience in <b>AWS, Docker, Kubernetes</b>, and CI/CD pipelines.</p><p>You will design, build, and manage cloud infrastructure, streamline deployment processes, monitor system health, and proactively handle security incidents and suspicious activities. This role works closely with backend (NestJS), frontend (Angular), and QA teams to ensure secure and reliable delivery.</p><p>Key Responsibilities</p><ul><li>Design, deploy, and maintain <b>AWS infrastructure</b> for both monolithic and microservices-based applications using:</li><li>ECS/EKS, EC2, RDS, S3, CloudFront, and Lambda</li><li>Build and maintain <b>CI/CD pipelines</b> for:</li><li>NestJS (backend)</li><li>Angular (frontend)</li><li>Implement and manage <b>Infrastructure as Code (IaC)</b> using <b>Terraform or AWS CloudFormation</b></li><li>Set up and maintain <b>monitoring, logging, and alerting systems</b>, including:</li><li>CloudWatch, Prometheus, Grafana, ELK/EFK stacks</li><li>Containerize and orchestrate services using <b>Docker and Kubernetes</b> (EKS or self-managed clusters)</li><li>Ensure <b>infrastructure security, compliance, and data protection</b> across all environments</li><li>Monitor for suspicious activities and vulnerabilities, investigate alerts, and take proactive remediation actions</li><li>Implement identity and access management best practices, including:</li><li>Least-privilege access</li><li>Network segmentation</li><li>Secrets management (AWS Secrets Manager, Vault, etc.)</li><li>Automate deployments, scaling, and backups to improve <b>reliability and availability</b></li><li>Collaborate closely with backend, frontend, and QA teams to ensure <b>smooth, secure delivery</b></li><li>Participate in continuous improvement of DevOps and DevSecOps practices</li></ul><p>Required Skills</p><ul><li>5+ years of experience as a <b>DevOps Engineer, Cloud Engineer, or Site Reliability Engineer (SRE)</b></li><li>Strong proficiency with <b>AWS services</b>, including:</li><li>ECS/EKS, EC2, RDS, S3, CloudFront, Lambda, VPC, IAM</li><li>Expertise with <b>Docker</b> and solid understanding of <b>Kubernetes</b> concepts:</li><li>Deployments, services, ingress, scaling</li><li>Proven experience building and managing <b>CI/CD pipelines</b> using:</li><li>GitHub Actions, GitLab CI, or Jenkins</li><li>Strong scripting and automation skills:</li><li>Bash, Python, or Node.js</li><li>Experience with <b>Linux system administration</b> and network troubleshooting</li><li>Familiarity with <b>NestJS and Angular deployment lifecycles</b></li><li>Hands-on knowledge of <b>monitoring, logging, and incident response workflows</b></li><li>Awareness of <b>DevSecOps principles</b> and cloud security posture management</li></ul><p>Nice to Have</p><ul><li>AWS Certifications:</li><li>DevOps Engineer &ndash; Professional</li><li>Solutions Architect &ndash; Associate or Professional</li><li>Experience with <b>serverless architectures</b>:</li><li>AWS Lambda, API Gateway, Step Functions</li><li>Experience implementing <b>cost optimization</b> best practices and the <b>AWS Well-Architected Framework</b></li><li>Exposure to <b>container security and vulnerability scanning tools</b>:</li><li>Trivy, Aqua, Falco, or similar</li></ul><p>Soft Skills</p><ul><li>Strong <b>security mindset</b> with the ability to respond quickly to incidents</li><li>Excellent <b>problem-solving and analytical skills</b></li><li>Effective <b>communication and mentorship</b> abilities</li><li>Collaborative, proactive, and <b>continuous-improvement oriented</b></li><li>Passionate about <b>automation, scalability, and secure infrastructure</b></li></ul><p>Job Types: Full-time, Part-time, Permanent, Contract</p><p>Pay: E&pound;20,000.00 - E&pound;30,000.00 per month</p><p>Expected hours: 20 &ndash; 40 per week</p>

DevOps

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