Job Description & Summary: A career within Enterprise Architecture services, will provide you with the opportunity to bring our clients a competitive advantage through defining their technology objectives, assessing solution options, and devising architectural solutions that help them achieve both strategic goals and meet operational requirements. We help build software and design data platforms, manage large volumes of client data, develop compliance procedures for data management, and continually researching new technologies to drive innovation and sustainable change. 

Responsibilities: 

As a SRE Engineer, you will be responsible for building and setting up new development tools and infrastructure utilizing knowledge in continuous integration, delivery, and deployment (CI/CD), Cloud technologies, Container Orchestration and Security. Your typical day will involve building and testing end-to-end CI/CD pipelines, ensuring that systems are safe against security threats, and utilizing your expertise in UNIX Shell Scripting. 
 
Roles & Responsibilities: 
Design and implement end-to-end CI/CD pipelines utilizing tools such as Jenkins, Git, and Docker. 
Ensure the security of systems by implementing security measures such as firewalls, encryption, and access controls. 
Collaborate with cross-functional teams to identify and resolve issues related to infrastructure and deployment. 
Automate infrastructure deployment and management using tools such as Ansible, Chef, or Puppet. 
Monitor and optimize system performance, ensuring high availability and scalability of infrastructure. Professional & Technical Skills: 
Must To Have Skills: Expertise in UNIX Shell Scripting. 
Good To Have Skills: Knowledge of Cloud technologies such as AWS or Azure, Container Orchestration tools such as Kubernetes or Docker Swarm. 
Experience with continuous integration and delivery tools such as Jenkins or Git. 
Experience with infrastructure automation tools such as Ansible, Chef, or Puppet. 
Strong understanding of security measures such as firewalls, encryption, and access controls.  

Mandatory skill sets: 

Deep knowledge of Azure Machine Learning Studio, Azure Databricks, and Azure OpenAI Service. 
Programming: Strong Python programming skills for data manipulation and model creation.DevOps 
Tools: Expertise in Azure DevOps/GitHub Actions for automation. 
Frameworks: Familiarity with MLflow for experiment tracking and model packaging. 
Containerization: Proficiency with Docker and Kubernetes (AKS) for container orchestration. 

Preferred skill sets: 

Preferred to have certifications. 

Years of experience required: 

4+yrs exp 

Education qualification: 

B.E. / B.Tech / MCA/ M.E/ M.TECH/ MBA/ PGDM. All qualifications should be in regular full-time mode with no extension of course duration due to backlogs.