L04 - DevOps

Job Description

Purpose Senior DevOps engineer is responsible for automating and improving the collaboration between software development and IT operations teams, ensuring faster and more reliable software releases. Should be a quick learner with exposure to AIOps. DevOps, MLOps and some knowledge in CloudOps. and should be an expert in handling python & .Net based projects, docker, Kubernetes, podman. Job Tasks: » CI/CD Pipeline Management » Design, construct, install, test and maintain Infrastructure as Code » Containerization » Deployment and Release Management » Security Integrations » Automation and Scripting » Monitoring and Analytics » disaster recovery procedures Key Responsibilities Design, implement, and manage scalable and reliable infrastructure for GenAI-based applications. Collaborate with development teams to ensure seamless integration and deployment of GenAI models and services. Automate and optimize CI/CD pipelines to support rapid development and deployment cycles (multi cloud). Monitor and troubleshoot system performance, ensuring high availability and reliability of GenAI applications. Implement security best practices and ensure compliance with industry standards. Mentor and guide junior DevOps engineers, fostering a culture of continuous improvement and innovation. Stay updated with the latest trends and advancements in GenAI and DevOps technologies. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a DevOps Engineer, with a focus on GenAI-based implementations. Strong knowledge of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Proficiency in scripting and automation tools (Python, Bash, Ansible, Terraform). Experience with CI/CD tools (Jenkins, GitLab CI, CircleCI) and version control systems (Git). Solid understanding of networking, security, and system administration. Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment. Strong communication and leadership skills. Additional skills Experience with machine learning frameworks and libraries (TensorFlow, PyTorch). Knowledge of infrastructure as code (IaC) and configuration management. Familiarity with monitoring and logging tools (Prometheus, Grafana, Power BI, ELK stack). Recommend different ways to constantly improve data reliability and quality. Designing and building validation engines for monitoring of sourced data Processing, cleansing, and verifying the integrity of data used for analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Technical skills Mandatory » 4 to 8 years of experience as Data Engineer or Data Analyst » Graduate in Engineering, Technology, applied mathematics, physics statistics along with good business skills » Excellent understanding of Data Mining technologies, NOSQL databases, Web Scrapping. » Excellent understanding of data sourcing and validation algorithms » Experience of working in Cloud based infrastructure » Good scripting and programming skills in Python » Experience with NoSQL databases, such as MongoDB, Cassandra » Good, applied statistics skills, such as distributions, statistical testing, regression, etc. Nice to have » Exposure to financial research domain » Industry recognized certification programs on Data Management/Cloud etc. » Experience with JIRA, Confluence » Understanding of scrum and Agile methodologies » Experience with data visualization tools, such as Grafana, GGplot, etc. Soft skills » Oral and written communication skills » Good problem solving and negotiation skills » Intellectual curiosity to find new and unusual ways of how to solve data management issues. » Passionate about the work and attention to detail