707 Gitlab Ci Jobs - Page 28

Project description We are looking for a passionate and skilled Python Engineer with 3-4 years of hands-on experience in automation, continuous integration (CI), and DevOps practices. The ideal candidate should possess strong debugging and problem-solving skills, a good understanding of AI/LLM fundamentals, and the ability to work in a fast-paced environment within a global IT MNC. Responsibilities Develop and maintain Python-based automation scripts and tools. Implement and optimize CI/CD pipelines (e.g., Jenkins, GitLab CI, etc.). Collaborate with DevOps, QA, and product teams to streamline development workflows. Troubleshoot and debug issues across applications, tools, and infrastructure. Contribute to deployment strategies and environment setups. Leverage basic AI/LLM knowledge in automation use-cases (optional but preferred). Maintain and document reusable components and utilities. Skills Must have 3-4y exp Strong programming skills in Python. Experience with Automation Frameworks and scripting (e.g., Pytest, Fabric, Ansible, Shell scripting). Good understanding and hands-on experience with CI/CD tools: Jenkins, Git, GitLab CI, etc. Working knowledge of Linux/Unix environments and basic system administration. Good knowledge of debugging techniques and performance analysis tools. Basic understanding of AI/ML or LLM concepts, and exposure to frameworks like Hugging Face, OpenAI API, etc. is a plus. Nice to have Good communication skills and ability to collaborate across teams.

Deep expertise in CI/CD tools including, Copado or Jenkins , GitHub Actions, GitLab CI and Bitbucket Pipelines . Strong foundational and practical knowledge of DevOps Practices & release automation Proven ability in CI/CD Pipeline design & management Expertise in version control management Familiarity with various integration tools and middleware Strong collaboration with the development & QA teams Lead DevOps practices including automated testing, deployment, CI/CD pipeline management and release automation Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure (GCP, AWS etc.) Experience with logging, backup/restoration, and monitoring tools (e.g., Splunk, Odesava, Datadog) Excellent communication skills, strong aptitude, and positive attitude Experience working in an Agile environment

Project description We are looking for a highly skilled Murex Environment Consultant who can think out of the box and design an auto-scaling solution for our non-production environments. You will work closely with the Murex team to create scalable, efficient, and reliable systems that meet business and technical requirements. Responsibilities Experience working in Murex environments. Design, implement, and maintain auto-scaling solutions for non-production environments. Collaborate with Murex teams to integrate and optimize scaling capabilities. Manage and fine-tune Kubernetes clusters to ensure performance, reliability, and cost efficiency. Support and optimize application server setups and end-of-day (EOD) processes. Identify and troubleshoot environment bottlenecks, providing sustainable engineering solutions. Document solutions and provide knowledge transfer to support teams. Handles cloud Environment preparation, rebuild, upkeep, maintenance, and upgrade activities. Ensure cloud cost optimization. Skills Must have 8+ Years of experience in Murex Environment Management Must-Have Skills: 1.Strong Kubernetes Expertise Experience deploying and managing applications in Kubernetes clusters Understanding of auto-scaling strategies (HPA, VPA, Cluster Autoscaler) Hands-on experience with Helm, ConfigMaps, Secrets, and service discovery 2.Infrastructure Engineering & Solutioning Proven experience designing and implementing environment automation or optimization solutions Ability to think innovatively and engineer custom solutions for complex setups 3.Murex Environment Experience Familiarity with Murex application architecture (EOD processes, batch jobs, Murex settings, Parameters and configurations, etc.) Understanding of dependencies and server orchestration in a Murex environment Hands-on knowledge of application server configurations Understanding of End-of-Day (EOD) process flows Scripting (Perl, awk), SQL, Unix XML, RDMS Operation Knowledge of Scheduling tool such as control M, Autosys 4.DevOps & Automation Tools Experience with CI/CD tools (Jenkins, GitLab CI, etc.) Familiarity with scripting (bash, ant, Python/Perl scripts on LINUX RHEL etc.) to automate operational tasks 5.Cloud & Container Platforms Exposure to public cloud environments (AWS, GCP, or Azure) Experience in container orchestration, resource management, and monitoring 6.Problem Solving & Out-of-the-Box Thinking Ability to approach environment engineering challenges creatively Track record of independently driving POCs or automation initiatives Nice to have Familiarity with cloud-based auto-scaling (AWS, Azure, or GCP) Experience with Murex C2/ openconnect would be an added advantage

Project description We are looking for a highly skilled Murex Environment Consultant who can think out of the box and design an auto-scaling solution for our non-production environments. You will work closely with the Murex team to create scalable, efficient, and reliable systems that meet business and technical requirements. Responsibilities Experience working in Murex environments. Design, implement, and maintain auto-scaling solutions for non-production environments. Collaborate with Murex teams to integrate and optimize scaling capabilities. Manage and fine-tune Kubernetes clusters to ensure performance, reliability, and cost efficiency. Support and optimize application server setups and end-of-day (EOD) processes. Identify and troubleshoot environment bottlenecks, providing sustainable engineering solutions. Document solutions and provide knowledge transfer to support teams. Handles cloud Environment preparation, rebuild, upkeep, maintenance, and upgrade activities. Ensure cloud cost optimization. Skills Must have 8+ Years of experience in Murex Environment Management Must-Have Skills: 1.Strong Kubernetes Expertise Experience deploying and managing applications in Kubernetes clusters Understanding of auto-scaling strategies (HPA, VPA, Cluster Autoscaler) Hands-on experience with Helm, ConfigMaps, Secrets, and service discovery 2.Infrastructure Engineering & Solutioning Proven experience designing and implementing environment automation or optimization solutions Ability to think innovatively and engineer custom solutions for complex setups 3.Murex Environment Experience Familiarity with Murex application architecture (EOD processes, batch jobs, Murex settings, Parameters and configurations, etc.) Understanding of dependencies and server orchestration in a Murex environment Hands-on knowledge of application server configurations Understanding of End-of-Day (EOD) process flows Scripting (Perl, awk), SQL, Unix XML, RDMS Operation Knowledge of Scheduling tool such as control M, Autosys 4.DevOps & Automation Tools Experience with CI/CD tools (Jenkins, GitLab CI, etc.) Familiarity with scripting (bash, ant, Python/Perl scripts on LINUX RHEL etc.) to automate operational tasks 5.Cloud & Container Platforms Exposure to public cloud environments (AWS, GCP, or Azure) Experience in container orchestration, resource management, and monitoring 6.Problem Solving & Out-of-the-Box Thinking Ability to approach environment engineering challenges creatively Track record of independently driving POCs or automation initiatives Nice to have Familiarity with cloud-based auto-scaling (AWS, Azure, or GCP) Experience with Murex C2/ openconnect would be an added advantage

Project description We are seeking a highly skilled Senior QA Engineer - Data Automation to lead the design and implementation of automated testing frameworks for our web-based platforms. You will be responsible for building scalable and reusable test suites using Playwright with Python, integrating them into CI/CD workflows, and ensuring robust quality coverage across our applications. This role is ideal for someone passionate about test automation, continuous improvement, and working in a fast-paced, collaborative Agile environment. Responsibilities Design and implement robust, scalable, and reusable test automation frameworks using Playwright with Python. Write end-to-end test cases for web applications, covering functional and regression testing. Integrate test automation into CI/CD pipelines (e.g., Jenkins, GitLab CI). Collaborate closely with developers, product managers, and other QA engineers in agile teams. Identify, document, and track bugs; work with development teams to resolve issues. Perform root cause analysis of test failures and improve automation stability. Continuously improve test coverage and automation efficiency. Skills Must have Experience: At least 6+ years in software QA, with 4+ years in test automation using Python. Automation Tools: Deep experience with Playwright. Programming: Strong Python programming skills, particularly in writing modular, reusable code for test automation. CI/CD: Hands-on experience integrating tests into pipelines using tools like Jenkins, GitLab CI, CircleCI, etc. Testing Knowledge: Solid understanding of QA methodologies, SDLC/STLC, and test management. Experience with functional, regression, integration, and UI testing. Collaboration & Tools: Experience using tools like JIRA, TestRail, or Xray for defect and test case management. Familiarity with version control systems (e.g., Git). Strong communication and collaboration skills to work across Agile teams.

Project description We are looking for a passionate and skilled Python Engineer with 3-4 years of hands-on experience in automation, continuous integration (CI), and DevOps practices. The ideal candidate should possess strong debugging and problem-solving skills, a good understanding of AI/LLM fundamentals, and the ability to work in a fast-paced environment within a global IT MNC. Responsibilities Develop and maintain Python-based automation scripts and tools. Implement and optimize CI/CD pipelines (e.g., Jenkins, GitLab CI, etc.). Collaborate with DevOps, QA, and product teams to streamline development workflows. Troubleshoot and debug issues across applications, tools, and infrastructure. Contribute to deployment strategies and environment setups. Leverage basic AI/LLM knowledge in automation use-cases (optional but preferred). Maintain and document reusable components and utilities. Skills Must have 3-4y exp Strong programming skills in Python. Experience with Automation Frameworks and scripting (e.g., Pytest, Fabric, Ansible, Shell scripting). Good understanding and hands-on experience with CI/CD tools: Jenkins, Git, GitLab CI, etc. Working knowledge of Linux/Unix environments and basic system administration. Good knowledge of debugging techniques and performance analysis tools. Basic understanding of AI/ML or LLM concepts, and exposure to frameworks like Hugging Face, OpenAI API, etc. is a plus. Nice to have Good communication skills and ability to collaborate across teams.

Project description Service Control own service management process definition, standardization and implementation, As an IT Change Enablement Expert, you will also be driving the adaptation of the Change Enablement process to align to the Continuous Integration and Continuous Delivery requirements. Also, you will have the opportunity to liaise with experts to align the Change Enablement process to the new automation concepts. Responsibilities Develop Change Enablement digital strategy processes with key delivery areas of continuous integration / continuous delivery, devops, automation and data analytics evolution Manage and deliver the day to day change enablement workflow tasks with the team such as: reviews, approvals ensuring risk controls are adhered to. Prepare deep dive data analytics and change reporting leading into relevant Governance meetings Engage and collaborate with the relevant Release Managers, Engineering, Operational Risk and Audit teams and drive delivery of tasks in the context of Change Enablement. Proactively identify operational readiness and change enablement process improvement opportunities. Skills Must have Experience in IT Change Enablement/Change Management for large organizations ITIL 3 or 4 experience and proficient with Microsoft suite of tools A thorough understanding of risks involved in the System Delivery Lifecycle (SDLC) and change environments Knowledge of the Continuous Integration and Continuous Delivery concepts and toolsets such as ServiceNow, Gitlab Familiarity with devops, agile methodologies and ways of working Strong analytical, reporting and data manipulation skills Attention to detail in all tasks, particularly in identifying gaps in operational processes areas Programming and/or automation skills (irrespective of toolset / technology) An enthusiastic and dynamic team player who is able to integrate and work successfully in a global team An excellent communicator, with strong interpersonal and stakeholder management skills Quick to produce accurate, concise information to tight deadlines, and to present that information professionally and in the right way to the required audience Excellent team player with a "can-do" attitude A balance of engineering and service mindset Experience of ServiceNow and M365 suite tooling Nice to have DevOps foundation certified is nice to have Experience of Gitlab CI/CD, AI tooling (CoPilot etc) and reporting platforms e.g PowerBi would be a benefit but not essential

Project description We are seeking a highly skilled Senior QA Engineer - Data Automation to lead the design and implementation of automated testing frameworks for our web-based platforms. You will be responsible for building scalable and reusable test suites using Playwright with Python, integrating them into CI/CD workflows, and ensuring robust quality coverage across our applications. This role is ideal for someone passionate about test automation, continuous improvement, and working in a fast-paced, collaborative Agile environment. Responsibilities Design and implement robust, scalable, and reusable test automation frameworks using Playwright with Python. Write end-to-end test cases for web applications, covering functional and regression testing. Integrate test automation into CI/CD pipelines (e.g., Jenkins, GitLab CI). Collaborate closely with developers, product managers, and other QA engineers in agile teams. Identify, document, and track bugs; work with development teams to resolve issues. Perform root cause analysis of test failures and improve automation stability. Continuously improve test coverage and automation efficiency. Skills Must have Experience: At least 6+ years in software QA, with 4+ years in test automation using Python. Automation Tools: Deep experience with Playwright. Programming: Strong Python programming skills, particularly in writing modular, reusable code for test automation. CI/CD: Hands-on experience integrating tests into pipelines using tools like Jenkins, GitLab CI, CircleCI, etc. Testing Knowledge: Solid understanding of QA methodologies, SDLC/STLC, and test management. Experience with functional, regression, integration, and UI testing. Collaboration & Tools: Experience using tools like JIRA, TestRail, or Xray for defect and test case management. Familiarity with version control systems (e.g., Git). Strong communication and collaboration skills to work across Agile teams. Nice to have N/A

Overview We are looking for an experienced API Test Engineer to join our quality assurance team. As an API Tester, you will be responsible for ensuring the functionality, reliability, and performance of application programming interfaces (APIs) used in our software products. You will work closely with developers, product managers, and business stakeholders to validate the design and functionality of APIs and ensure they meet the required specifications. Responsibilities Design, develop, and execute test cases for RESTful APIs. Perform functional, performance, security, and regression testing on APIs. Write automated test scripts for APIs using tools like Postman or JMeter. Monitor and evaluate API responses, ensuring they meet performance and functional criteria. Collaborate with developers and product managers to identify and resolve issues. Report, track, and prioritize defects using bug-tracking tools (e.g., Azure DevOps). Perform integration testing to ensure smooth communication between different system components. Ensure compliance with API standards, guidelines, and best practices. Create and maintain test data to support API testing. Provide recommendations for improving the quality and efficiency of the testing process. Qualifications Bachelor's degree in Computer Science, Information Technology, or related field. 2-3 years’ experience in API testing (preferred) or Application Testing. 1-2 years’ experience in test automation. Certifications (good to have): ISTQB/ CSTE/ CSQA etc. Knowledge of API documentation tools like Swagger or RAML. Experience with CI/CD pipeline and tools (e.g., Jenkins, GitLab CI). Familiarity with cloud platforms (e.g., Azure ) and containerization (e.g., Docker ).

Education Qualification: Bachelor's degree in computer science or related field or higher with minimum4 years of relevant experience. Position Description: We are looking for a proactive and skilled Mid-Level DevOps Engineer to join our growing team and support cutting-edge AI-driven initiatives. This role is critical to building and maintaining scalable, reliable infrastructure for machine learning models and data-intensive applications. The ideal candidate will bring strong DevOps expertise, hands-on experience with cloud platforms, CI/CD, and a solid understanding of AI/ML workflows. Your future duties and responsibilities: Design and maintain CI/CD pipelines for AI/ML model training, testing, and deployment. Manage cloud infrastructure (AWS, GCP, or Azure) optimized for AI workloads. Automate infrastructure provisioning using Terraform, CloudFormation, or Ansible. Support containerization (Docker) and orchestration (Kubernetes) of ML services. Implement monitoring and alerting solutions (Prometheus, Grafana, ELK, Datadog). Collaborate with AI teams to streamline workflows and ensure production readiness. Ensure scalability, performance, and security across DevOps practices. Troubleshoot infrastructure issues and conduct root cause analysis. Required qualifications to be successful in this role: Must-Have: 45 years in a DevOps role, preferably supporting AI/ML systems. Experience with CI/CD tools (Jenkins, GitLab CI/CD, CircleCI). Proficiency in Infrastructure as Code (Terraform, Ansible, CloudFormation). Hands-on expertise with Docker and Kubernetes in production. Cloud platform experience (AWS, GCP, or Azure). Strong scripting skills (Bash, Python). Familiarity with monitoring tools (Prometheus, Grafana, ELK Stack, or Datadog). Good-to-Have: Experience with ML tools like MLflow, Kubeflow, SageMaker, or DVC. Familiarity with AI/ML pipeline design and model versioning. Understanding of security best practices in cloud DevOps environments. Skills: Ansible BASH English Grafana Jenkins Kubernetes Prometheus Python Terraform HashiCorp Cert Terraform Assoc Kubernetes Administrator

Education Qualification: Any graduation or related field or higher with minimum 3 years of relevant experience. Position Description: We are seeking a highly skilled Integration Developer with strong expertise in Java (JDK 17), Spring Boot, Angular and solid experience working with Oracle databases and SQL. The ideal candidate is a problem solver who can translate high-level architectural solutions into robust, scalable code.Proficiency in Linux, CI/CD practices, and unit testing (JUnit) is essential. Familiar in working with deployments, servers (web security ,protocols ), scripting Experience with Scripting is a plus. Your future duties and responsibilities: Ability to take responsibility of application services including development , managing, deploying and Solution real time problems related to bugs, performance ,infrastructure and added new features Design, develop, and maintain high-quality backend applications using Java ,Spring Boot (JDK 17),Web/REST services . Collaborate with architects and stakeholders to understand high-level requirements and translate them into working solutions. Write optimized SQL queries and work extensively with Oracle databases. Develop and execute comprehensive unit tests using JUnit to ensure code quality and reliability. Work on multi-threaded applications and debug complex issues in distributed systems. Collaborate with DevOps teams to implement and maintain CI/CD pipelines. Write and maintain scripts using Groovy (nice to have). Operate efficiently in a Linux-based environment. Ensure attention to detail in code, documentation, and communication. Participate in code reviews and mentor junior team members. Communicate effectively with cross-functional teams to clarify requirements and present solutions. Required qualifications to be successful in this role: Must Have SKills Strong experience with Java (JDK 17) and Spring Boot Proficient in Oracle, SQL, and writing complex queries Comfortable working in Linux environments Strong grasp of multithreading, concurrency, and debugging Solid understanding of JUnit and unit testing best practices Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions) Excellent problem-solving skills and ability to work independently High level of attention to detail Strong communication skills Skills: Hibernate Java Enterprise Editions JEE RESTful (Rest-APIs) SCRUM Spring Spring Boot

Must have 6+ years of experience in intertwining security measures within DevOps practices. You will be pivotal in bolstering the security posture by embedding robust security frameworks into CI/CD pipelines and optimizing post-scan workflows. Your role will support a critical mission to enhance vulnerability assessment methodologies, swiftly triage security findings, and spearhead initiatives to uplift security standards across diverse development and infrastructure environments. Youll get to integrate and automate security tools, such as SAST, DAST, software composition analysis, and container scanning into a seamless CI/CD process to create a culture of security-first development. Participating actively in the management of post-scan activities will include: Triage findings with a focus on risk-based prioritization for vulnerabilities. Collaborate with development teams to track remediation status and ensure timely resolutions. Additionally, you will perform and support comprehensive vulnerability assessments for both application and infrastructure assets. Your responsibilities will involve close collaboration with DevOps and Security teams to establish and enforce effective security practices that dovetail with agile methodologies. Leverage your expertise to develop workflows that ensure secure builds, artifact signing, and automating secure release processes, enhancing our operational efficiency. You will also configure and manage infrastructure as code (IaC) tools such as Terraform and Ansible, embedding security controls to safeguard our automation processes. Monitoring, logging, and alerting mechanisms will be part of your project to establish a strong security monitoring strategy for all deployed workloads, ensuring rapid response to potential threats. Your contributions will not just stop at implementation; youll be responsible for generating insightful reports, metrics, and dashboards to track security posture and compliance across multiple environments. Required Skills & Experience: A minimum of 6 years experience in DevOps and Security Engineering roles, showcasing a strong foundation in both domains. Proficient in integrating security tools such as SonarQube, Fortify, Checkmarx, and others to create a robust security framework. Solid understanding of CI/CD practices using tools like Jenkins, GitLab CI, and GitHub Actions, paired with modern source control management workflows. Expertise in vulnerability management, understanding of CVSS scoring, and risk assessment methodologies that align with best practices. Experienced with widespread cloud platforms like AWS, Azure, and GCP, especially their security features and compliance landscapes. Familiar with container ecosystems, notably Docker and Kubernetes along with runtime scanning practices to ensure container security capabilities. Mandatory Skills: Vulnerability Assessment Penetrationtest. Experience: 8-10 Years.

Develop and maintain automation test scripts using tools like Selenium, TestNG, JUnit, or similar. Integrate automated tests with CI/CD pipelines (e.g., Jenkins, GitLab CI). Collaborate with development and QA teams to define test strategies Required Candidate profile Proficiency in automation tools (e.g., Selenium, Appium). Strong programming skills in Java/Python/C#. Experience with test frameworks like TestNG, JUnit, or similar. Knowledge of CI/CD tools

Deep expertise in CI/CD tools including, Copado or Jenkins , GitHub Actions, GitLab CI and Bitbucket Pipelines . Strong foundational and practical knowledge of DevOps Practices & release automation Proven ability in CI/CD Pipeline design & management Expertise in version control management Familiarity with various integration tools and middleware Strong collaboration with the development & QA teams Lead DevOps practices including automated testing, deployment, CI/CD pipeline management and release automation Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure (GCP, AWS etc.) Experience with logging, backup/restoration, and monitoring tools (e.g., Splunk, Odesava, Datadog) Excellent communication skills, strong aptitude, and positive attitude Experience working in an Agile environment.

Project description We are looking for a highly skilled Murex Environment Consultant who can think out of the box and design an auto-scaling solution for our non-production environments. You will work closely with the Murex team to create scalable, efficient, and reliable systems that meet business and technical requirements. Responsibilities Experience working in Murex environments. Design, implement, and maintain auto-scaling solutions for non-production environments. Collaborate with Murex teams to integrate and optimize scaling capabilities. Manage and fine-tune Kubernetes clusters to ensure performance, reliability, and cost efficiency. Support and optimize application server setups and end-of-day (EOD) processes. Identify and troubleshoot environment bottlenecks, providing sustainable engineering solutions. Document solutions and provide knowledge transfer to support teams. Handles cloud Environment preparation, rebuild, upkeep, maintenance, and upgrade activities. Ensure cloud cost optimization. Skills Must have 8+ Years of experience in Murex Environment Management Must-Have Skills: 1.Strong Kubernetes Expertise Experience deploying and managing applications in Kubernetes clusters Understanding of auto-scaling strategies (HPA, VPA, Cluster Autoscaler) Hands-on experience with Helm, ConfigMaps, Secrets, and service discovery 2.Infrastructure Engineering & Solutioning Proven experience designing and implementing environment automation or optimization solutions Ability to think innovatively and engineer custom solutions for complex setups 3.Murex Environment Experience Familiarity with Murex application architecture (EOD processes, batch jobs, Murex settings, Parameters and configurations, etc.) Understanding of dependencies and server orchestration in a Murex environment Hands-on knowledge of application server configurations Understanding of End-of-Day (EOD) process flows Scripting (Perl, awk), SQL, Unix XML, RDMS Operation Knowledge of Scheduling tool such as control M, Autosys 4.DevOps & Automation Tools Experience with CI/CD tools (Jenkins, GitLab CI, etc.) Familiarity with scripting (bash, ant, Python/Perl scripts on LINUX RHEL etc.) to automate operational tasks 5.Cloud & Container Platforms Exposure to public cloud environments (AWS, GCP, or Azure) Experience in container orchestration, resource management, and monitoring 6.Problem Solving & Out-of-the-Box Thinking Ability to approach environment engineering challenges creatively Track record of independently driving POCs or automation initiatives Nice to have Familiarity with cloud-based auto-scaling (AWS, Azure, or GCP) Experience with Murex C2/ openconnect would be an added advantage

Project description We are seeking a highly skilled Senior QA Engineer - Data Automation to lead the design and implementation of automated testing frameworks for our web-based platforms. You will be responsible for building scalable and reusable test suites using Playwright with Python, integrating them into CI/CD workflows, and ensuring robust quality coverage across our applications. This role is ideal for someone passionate about test automation, continuous improvement, and working in a fast-paced, collaborative Agile environment. Responsibilities Design and implement robust, scalable, and reusable test automation frameworks using Playwright with Python. Write end-to-end test cases for web applications, covering functional and regression testing. Integrate test automation into CI/CD pipelines (e.g., Jenkins, GitLab CI). Collaborate closely with developers, product managers, and other QA engineers in agile teams. Identify, document, and track bugs; work with development teams to resolve issues. Perform root cause analysis of test failures and improve automation stability. Continuously improve test coverage and automation efficiency. Skills Must have Experience: At least 6+ years in software QA, with 4+ years in test automation using Python. Automation Tools: Deep experience with Playwright. Programming: Strong Python programming skills, particularly in writing modular, reusable code for test automation. CI/CD: Hands-on experience integrating tests into pipelines using tools like Jenkins, GitLab CI, CircleCI, etc. Testing Knowledge: Solid understanding of QA methodologies, SDLC/STLC, and test management. Experience with functional, regression, integration, and UI testing. Collaboration & Tools: Experience using tools like JIRA, TestRail, or Xray for defect and test case management. Familiarity with version control systems (e.g., Git). Strong communication and collaboration skills to work across Agile teams. Nice to have N/A

A hands-on engineering position responsible for designing, automating, and maintaining robust build systems and deployment pipelines for AI/ML components, with direct development responsibilities in C++ and Python. The role supports both model training infrastructure and high-performance inference systems. Design and implement robustbuild automation systemsthat support large, distributed AI/C++/Python codebases. Develop tools and scripts that enable developers and researchers to rapidly iterate, test, and deploy across diverse environments. Integrate C++ components with Python-based AI workflows, ensuring compatibility, performance, and maintainability. Lead the creation ofportable, reproducible development environments, ensuring parity between development and production. Maintain and extend CI/CD pipelines for Linux and z/OS, implementing best practices in automated testing, artifact management, and release validation. Collaborate with cross-functional teams — including AI researchers, system architects, and mainframe engineers — to align infrastructure with strategic goals. Proactively monitor and improve build performance, automation coverage, and system reliability. Contribute to internal documentation, process improvements, and knowledge sharing to scale your impact across teams. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Strong programming skills in C++ and Python, with a deep understanding of both compiled and interpreted language paradigms. Hands-on experience building and maintainingcomplex automation pipelines(CI/CD) using tools likeJenkins, or GitLab CI. In-depth experience withbuild tools and systemssuch asCMake, Make, Meson, or Ninja, including custom script development and cross-compilation. Experience working onmulti-platform development, specifically onLinux and IBM z/OSenvironments, including understanding of their respective toolchains and constraints. Experience integratingnative C++ code with Python, leveragingpybind11,Cython, or similar tools for high-performance interoperability. Proven ability to troubleshoot and resolvebuild-time, runtime, and integration issuesin large-scale, multi-component systems. Comfortable withshell scripting(Bash, Zsh, etc.) and system-level operations. Familiarity withcontainerization technologieslike Docker for development and deployment environments Preferred technical and professional experience Working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, or ONNX, including understanding of how they integrate into production environments. Experience developing or maintaining software on IBM z/OS mainframe systems. Familiarity with z/OS build and packaging workflows, Understanding of system performance tuning, especially in high-throughput compute or I/O environments (e.g., large model training or inference). Knowledge of GPU computing and low-level profiling/debugging tools. Experience managing long-lifecycle enterprise systems and ensuring compatibility across releases and deployments. Background contributing to or maintaining open-source projects in the infrastructure, DevOps, or AI tooling space Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects.

A hands-on engineering position responsible for designing, automating, and maintaining robust build systems and deployment pipelines for AI/ML components, with direct development responsibilities in C++ and Python. The role supports both model training infrastructure and high-performance inference systems. Design and implement robustbuild automation systemsthat support large, distributed AI/C++/Python codebases. Develop tools and scripts that enable developers and researchers to rapidly iterate, test, and deploy across diverse environments. Integrate C++ components with Python-based AI workflows, ensuring compatibility, performance, and maintainability. Lead the creation ofportable, reproducible development environments, ensuring parity between development and production. Maintain and extend CI/CD pipelines for Linux and z/OS, implementing best practices in automated testing, artifact management, and release validation. Collaborate with cross-functional teams — including AI researchers, system architects, and mainframe engineers — to align infrastructure with strategic goals. Proactively monitor and improve build performance, automation coverage, and system reliability. Contribute to internal documentation, process improvements, and knowledge sharing to scale your impact across teams Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 5+ years of strong programming skills in C++ and Python, with a deep understanding of both compiled and interpreted language paradigms. Hands-on experience building and maintainingcomplex automation pipelines(CI/CD) using tools likeJenkins, or GitLab CI. In-depth experience withbuild tools and systemssuch asCMake, Make, Meson, or Ninja, including custom script development and cross-compilation. Experience working onmulti-platform development, specifically onLinux and IBM z/OSenvironments, including understanding of their respective toolchains and constraints. Experience integratingnative C++ code with Python, leveragingpybind11,Cython, or similar tools for high-performance interoperability. Proven ability to troubleshoot and resolvebuild-time, runtime, and integration issuesin large-scale, multi-component systems. Comfortable withshell scripting(Bash, Zsh, etc.) and system-level operations. Familiarity withcontainerization technologieslike Docker for development and deployment environments. Preferred technical and professional experience Working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, or ONNX, including understanding of how they integrate into production environments. Experience developing or maintaining software on IBM z/OS mainframe systems. Familiarity with z/OS build and packaging workflows, Understanding of system performance tuning, especially in high-throughput compute or I/O environments (e.g., large model training or inference). Knowledge of GPU computing and low-level profiling/debugging tools. Experience managing long-lifecycle enterprise systems and ensuring compatibility across releases and deployments. Background contributing to or maintaining open-source projects in the infrastructure, DevOps, or AI tooling space Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects.

Educational Requirements Master Of Engineering,Master Of Science,MCA,MTech,Bachelor Of Science,Bachelor of Engineering,BCA,BE,BTech Service Line Application Development and Maintenance Responsibilities Design and implement cloud-native solutions on Google Cloud PlatformDeploy and manage infrastructure using Terraform, Cloud Deployment Manager, or similar IaC toolsManage GCP services such as Compute Engine, GKE (Kubernetes), Cloud Storage, Pub/Sub, Cloud Functions, BigQuery, etc.Optimize cloud performance, cost, and scalabilityEnsure security best practices and compliance across the GCP environmentMonitor and troubleshoot issues using Stackdriver/Cloud MonitoringCollaborate with development, DevOps, and security teamsAutomate workflows, CI/CD pipelines using tools like Jenkins, GitLab CI, or Cloud Build Additional Responsibilities: GCP Professional certification (e.g., Professional Cloud Architect, Cloud Engineer)Experience with hybrid cloud or multi-cloud architectureExposure to other cloud platforms (AWS/Azure) is a plusStrong communication and teamwork skills Technical and Professional Requirements: 3–5 years of hands-on experience with GCPStrong expertise in Terraform, GCP networking, and cloud securityProficient in container orchestration using Kubernetes (GKE)Experience with CI/CD, DevOps practices, and shell scripting or PythonGood understanding of IAM, VPC, firewall rules, and service accountsFamiliarity with monitoring/logging tools like Stackdriver or PrometheusStrong problem-solving and troubleshooting skills Preferred Skills: .Net Java Python Java-Springboot Cloud Platform -Google Cloud Platform Developer-GCP/ Google Cloud

A hands-on engineering position responsible for designing, automating, and maintaining robust build systems and deployment pipelines for AI/ML components, with direct development responsibilities in C++ and Python. The role supports both model training infrastructure and high-performance inference systems. Design and implement robustbuild automation systemsthat support large, distributed AI/C++/Python codebases. Develop tools and scripts that enable developers and researchers to rapidly iterate, test, and deploy across diverse environments. Integrate C++ components with Python-based AI workflows, ensuring compatibility, performance, and maintainability. Lead the creation ofportable, reproducible development environments, ensuring parity between development and production. Maintain and extend CI/CD pipelines for Linux and z/OS, implementing best practices in automated testing, artifact management, and release validation. Collaborate with cross-functional teams — including AI researchers, system architects, and mainframe engineers — to align infrastructure with strategic goals. Proactively monitor and improve build performance, automation coverage, and system reliability. Contribute to internal documentation, process improvements, and knowledge sharing to scale your impact across teams Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise With 5+ years of strong programming skills in C++ and Python, with a deep understanding of both compiled and interpreted language paradigms. Hands-on experience building and maintainingcomplex automation pipelines(CI/CD) using tools likeJenkins, or GitLab CI. In-depth experience withbuild tools and systemssuch asCMake, Make, Meson, or Ninja, including custom script development and cross-compilation. Experience working onmulti-platform development, specifically onLinux and IBM z/OSenvironments, including understanding of their respective toolchains and constraints. Experience integratingnative C++ code with Python, leveragingpybind11,Cython, or similar tools for high-performance interoperability. Proven ability to troubleshoot and resolvebuild-time, runtime, and integration issuesin large-scale, multi-component systems. Comfortable withshell scripting(Bash, Zsh, etc.) and system-level operations. Familiarity withcontainerization technologieslike Docker for development and deployment environments. Preferred technical and professional experience Working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, or ONNX, including understanding of how they integrate into production environments. Experience developing or maintaining software on IBM z/OS mainframe systems. Familiarity with z/OS build and packaging workflows, Understanding of system performance tuning, especially in high-throughput compute or I/O environments (e.g., large model training or inference). Knowledge of GPU computing and low-level profiling/debugging tools. Experience managing long-lifecycle enterprise systems and ensuring compatibility across releases and deployments. Background contributing to or maintaining open-source projects in the infrastructure, DevOps, or AI tooling space Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects

Ansible Automation - DR.We are looking for a highly skilled Infrastructure SpecialistRed Hat DevOps to lead and support infrastructure automation initiatives using Ansible and other DevOps tools. This role will focus on automating enterprise Red Hat Enterprise Linux (RHEL) and Red Hat OpenShift (OCP) environments, integrating multiple tools with automation pipelines, and sequencing disaster recovery (DR) automation workflows using Ansible. You will play a key role in designing resilient, automated infrastructure solutions that support both operational excellence and business continuity. Develop and maintain Ansible automation scripts and playbooks for RHEL and OpenShift platforms. Experience in working with teams to prioritize work Integrate monitoring, backup. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 6+ years of experience in design and delivery of complex and large-scale IT projects.Expertise in the DevOps Lead - GitLab, CheckMarx , Nexus.The CI/CD Engineer (GitLab Specialist) is responsible for designing, implementing, and maintaining continuous integration and continuous deployment (CI/CD) pipelines using GitLab CI/CD.Candidates with strong experience in Banking and Financial services will also be considered. This role ensures fast, reliable, and secure software delivery by automating build, test, and deployment processes. The engineer collaborates with development, QA, and operations teams to streamline workflows and improve deployment efficiency Design, implement, and maintain GitLab CI/CD pipelines for build, test, and deployment automation. Optimize pipelines for speed, reliability, and cost-efficiency (caching, parallel jobs, artifacts management). Preferred technical and professional experience Experience leading projects delivered through a globally integrated capability of onsite, nearshore, and offshore teams. Experience with Agile methods & DevOps. Experience in design and delivery of scalable, fault tolerant and resilient systems Familiar with data center concepts and best practices, high - availability systems, capacity planning, system performance evaluation, and diagnostic techniques and methodologies.

A hands-on engineering position responsible for designing, automating, and maintaining robust build systems and deployment pipelines for AI/ML components, with direct development responsibilities in C++ and Python. The role supports both model training infrastructure and high-performance inference systems. Design and implement robustbuild automation systemsthat support large, distributed AI/C++/Python codebases. Develop tools and scripts that enable developers and researchers to rapidly iterate, test, and deploy across diverse environments. Integrate C++ components with Python-based AI workflows, ensuring compatibility, performance, and maintainability. Lead the creation ofportable, reproducible development environments, ensuring parity between development and production. Maintain and extend CI/CD pipelines for Linux and z/OS, implementing best practices in automated testing, artifact management, and release validation. Collaborate with cross-functional teams — including AI researchers, system architects, and mainframe engineers — to align infrastructure with strategic goals. Proactively monitor and improve build performance, automation coverage, and system reliability. Contribute to internal documentation, process improvements, and knowledge sharing to scale your impact across teams. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Strong programming skills in C++ and Python, with a deep understanding of both compiled and interpreted language paradigms. Hands-on experience building and maintainingcomplex automation pipelines(CI/CD) using tools likeJenkins, or GitLab CI. In-depth experience withbuild tools and systemssuch asCMake, Make, Meson, or Ninja, including custom script development and cross-compilation. Experience working onmulti-platform development, specifically onLinux and IBM z/OSenvironments, including understanding of their respective toolchains and constraints. Experience integratingnative C++ code with Python, leveragingpybind11,Cython, or similar tools for high-performance interoperability. Proven ability to troubleshoot and resolvebuild-time, runtime, and integration issuesin large-scale, multi-component systems. Comfortable withshell scripting(Bash, Zsh, etc.) and system-level operations. Familiarity withcontainerization technologieslike Docker for development and deployment environments Preferred technical and professional experience Working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, or ONNX, including understanding of how they integrate into production environments. Experience developing or maintaining software on IBM z/OS mainframe systems. Familiarity with z/OS build and packaging workflows, Understanding of system performance tuning, especially in high-throughput compute or I/O environments (e.g., large model training or inference). Knowledge of GPU computing and low-level profiling/debugging tools. Experience managing long-lifecycle enterprise systems and ensuring compatibility across releases and deployments. Background contributing to or maintaining open-source projects in the infrastructure, DevOps, or AI tooling space Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects.

Role Purpose The purpose of this role is to lead DevOps team to facilitate better coordination among operations, development and testing functions by automating and streamlining the integration and deployment processes Do 6 to 9 years of experience with minimum 2+ of experience with Kubernetes in designing, building and managing large scale production application infrastructure. Hands on experience in Google Cloud platform who will be responsible to Build, manage and support infrastructure in Google cloud platform. Hands on experience with large enterprise Linux/Unix production environment Hands on experience with Infrastructure-as-Code technologies: Terraform/Ansible/Puppet DevOps Experience with SCM, CI/CD systems (GitLab CI/CD) Experienced with deploying and operating services on Linux Mandatory skills Kubernetes GCP Linux Infrastructure-as-Code technologies Preferred any developer background Provide customer support/ service on the DevOps tools Timely support internal & external customers escalations on multiple platforms Troubleshoot the various problems that arise in implementation of DevOps tools across the project/ module Perform root cause analysis of major incidents/ critical issues which may hamper project timeliness, quality or cost Develop alternate plans/ solutions to be implemented as per root cause analysis of critical problems Follow escalation matrix/ process as soon as a resolution gets complicated or isnt resolved Provide knowledge transfer, sharing best practices with the team and motivate Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Train direct reportees to make right recruitment and selection decisions Talent Management Ensure 100% compliance to Wipros standards of adequate onboarding and training for team members to enhance capability & effectiveness Build an internal talent pool of HiPos and ensure their career progression within the organization Promote diversity in leadership positions Performance Management Set goals for direct reportees, conduct timely performance reviews and appraisals, and give constructive feedback to direct reports. Incase of performance issues, take necessary action with zero tolerance for will based performance issues Ensure that organizational programs like Performance Nxtarewell understood and that the team is taking the opportunities presented by such programs to their and their levels below Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Proactively challenge the team with larger and enriching projects/ initiatives for the organization or team Exercise employee recognition and appreciation Mandatory Skills: Kubernetes. Experience: 5-8 Years.

We are seeking an experienced Infrastructure Automation Engineer with a strong background in scripting and automation across both mainframe and distributed systems. The ideal candidate will have hands on experience with Python, Ansible , and infrastructure as code practices, and will play a key role in automating repetitive infrastructure tasks, enabling faster deployments, and ensuring consistency across environments. Primary Roles and Responsibilities: Design, develop, and maintain automation scripts and frameworks using Python and Ansible. Build infrastructure-as-code solutions to automate configuration, provisioning, and deployment of resources across mainframe and distributed platforms (e.g., Linux, Windows). Work closely with infrastructure, operations, and product(s) teams to understand automation needs and implement effective solutions. Develop and manage Ansible playbooks and custom roles for reusable automation. Contribute to configuration and change management processes in hybrid environments. Support hybrid environments including z/OS, Unix/Linux, Windows, and Cloud platforms (AWS, Azure, etc.). Document automation procedures, standards, and design decisions. To ensure youre set up for success, you will bring the following skillset & experience: Bachelors degree in Computer Science, Information Security, or related field (or equivalent experience). 3+ years of experience in infrastructure automation or DevOps roles. Strong proficiency in Python scripting for infrastructure-related tasks. Experience with Ansible for configuration management and orchestration. Hands on experience working with both Mainframe (z/OS) and Distributed Systems. Familiarity with infrastructure as code principles and practices. Experience with Git or other version control tools. Working knowledge of Linux system administration. Good understanding of job scheduling tools and system integrations. Strong analytical and problem-solving abilities. Ability to work independently and in a team across hybrid environments. Excellent communication and documentation skills. Willingness to learn legacy systems and contribute to their modernization. Whilst these are nice to have, our team can help you develop in the following skills: Familiarity with container technologies like Docker and orchestration using Kubernetes. Experience integrating automation into CI/CD pipelines (e.g., GitLab CI, Jenkins).

Knowledge of performance testing tools (e.g., JMeter, LoadRunner). Exposure to cloud-based testing platforms (e.g., BrowserStack, Sauce Labs). Familiarity with containerization (Docker) and orchestration (Kubernetes). Required Candidate profile Exp testing RESTful APIs using tools like Postman or REST Assured. Exp with BDD tools like Cucumber or Behave. Strong hands-on experience with Selenium WebDriver.