Job
Description
Position Overview: The AI CoE team is seeking an Infrastructure Engineering Lead Analyst to work on the AI ecosystem to build, deploy, and maintain robust infrastructure solutions within cloud environments, tailored for AI and machine learning workloads. This role involves a mix of innovative infrastructure design, hands-on deployment, and meticulous maintenance to ensure operational excellence in AI-powered applications. The work you do will impact millions of customers, members, and employers that rely on Cigna every day. Extreme focus on speed to market and getting Products and Services in the hands of customer and passion to transform healthcare is key to the success of this role. Responsibilities : Architect and deploy cloud infrastructure solutions that are secure, scalable, and optimized for AI and machine learning workloads. Collaborate with AI teams to understand computational needs and translate these into infrastructure requirements. Monitor, manage, and optimize cloud resources to maximize performance and minimize costs. Design and implement continuous integration and delivery pipelines for AI applications. Develop automation scripts and infrastructure as code to streamline deployment and management tasks. Maintain AI products on production environment. Expertise on AWS and Azure Coud and related technologies Expertise on CI/CD process using Jenkins/UDeploy/Git Expertise on various IDE (Integrated Development Environment) Contribute to architecture and capacity planning activities. Ensure data privacy, security and compliance standards are maintained, especially with sensitive or regulated data. Setup robust monitoring model performance, latency, resource usage and user feedback. Stay updated with latest tools and frameworks in GenAI infrastructure space and implement them to enhance performance/speed or cost-effectiveness. Qualifications : Required Skills: Good knowledge of cloud computing delivery models (IaaS, PaaS, and SaaS) and deployment models related to Public, Private and Hybrid Cloud service Prior experience required in IT Service Management - Incident Management, Problem Management, Change Management, ITIL Experience working with platform and products like Splunk, Dynatrace, OpenShift, Azure, AWS, ServiceNow, CMDB Proficient in Linux/UNIX or Windows environments, including scripting and administration. Familiarity with cloud data services and big data processing tools. Bachelors degree in computer science or software engineering 2+ years of relevant work experience in solutions design and engineering, Experience with containerization (Docker, Kubernetes) and cloud service providers (AWS, Azure, GCP). Strong automation development skills. Needs to be proficient in one or more automation languages [i. e. Ansible, Cloud Formations, Chef, Puppet, Terraform]. Strong background in network architecture, database programming (SQL/NoSQL), and data modelling. Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, Knowledge of routing/switching technologies. Proficiency in scripting languages (like Python, Bash, PowerShell) to automate tasks and manage infrastructure. Ability to analyse and enhance system performance and reliability. Required Experience & Education: 5-8 Years of Experience with at least 4 years in Production Support role in AI Domain. Experience working within the healthcare industry is desirable. Familiarity with healthcare-specific IT systems and industry regulations, such as Electronic Health Record systems and HIPAA, is an added advantage. Desired Experience: Exposure to Gen AI and Cloud systems like AWS. Location & Hours of Work Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH)
