Senior Full Stack Engineer - Cognitive Platform as a Service

Infra Tech Support Practitioner

Project Role : Infra Tech Support Practitioner
Project Role Description : Provide ongoing technical support and maintenance of production and development systems and software products (both remote and onsite) and for configured services running on various platforms (operating within a defined operating model and processes). Provide hardware/software support and implement technology at the operating system-level across all server and network areas, and for particular software solutions/vendors/brands. Work includes L1 and L2/ basic and intermediate level troubleshooting.
Must have skills : Application Lifecycle Management (ALM)
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education

Job Title: Senior FullStack Engineer - Cognitive Platform as a Service (PaaS). Summary We're looking for a visionary FullStack Engineers on cognitive systems on-prem HCIs, Private cloud and across public cloud stacks , to work on business critical client environments ,Cross technology Migrations , modernization solutions and technology crisis management. The focus is to manage client technology landscape and value add through innovation and address complex technical challenges faced by our clients Key Responsibilities: - Design, develop, and maintain end-to-end cognitive HCIs, Private cloud integrating intelligence into traditional web stacks. - Develop and manage full stack infrastructure Application including backend services (APIs, microservices) and API gateway for frontend and backend services. - Understand the impact of GPU based computing and have experience in deploying High Performance Computing environments - AWS Outpost, Azure Stack, Google cloud VPC Certified and implementation knowledge. - Tanzu, Red Hat Openshift cluster deployment on Private cloud Deisgn, Deploy and Maintain. - Develop cloud-native back-end services using Node.js, Python (FastAPI, Flask), or Java to connect AI models with application logic. - Integrate AI/ML models (TensorFlow, PyTorch, scikit-learn) into production-ready APIs and microservices. - Write efficient, maintainable code and manage integration between front-end interfaces and back-end infrastructure services. - Collaborate with product, design, ML, and DevOps teams to build intelligent workflows and user experiences - Implement Infrastructure as Code (IaC) using tools like Terraform, CloudFormation, AZURE DEV OPS or Pulumi. - Deploy and manage Platform-as-a-Service (PaaS) offerings. - Design, implement, and maintain database solutions, including relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, DynamoDB) - Collaborate with DevOps, security, and development teams to ensure seamless integration and delivery. - Ensure platform observability via metrics, logging, and monitoring frameworks (e.g., Prometheus, ELK, CloudWatch). - Manage containerization and orchestration using Docker and Kubernetes. - Ensure compliance with security best practices and organizational policies. - Continuously evaluate and implement new cloud technologies and tools to improve efficiency. - Provide technical guidance and support to team members and stakeholders. - Integrate and support AI-driven tools and frameworks, including Generative AI and Agentic AI technologies, within cloud infrastructure and applications. Required Skills: Systems Operatioms and Engineering - RHEL and SUSE and OLE and/or Wimdows/Hperv and/or AIX/HPUX/Soalris Hyper Converged Infrastructure and Private Cloud - Vmware/ Hyper V/ KVM//Pacemaker / AHV /OpenStack / Scale Computing / Nvidia Omniverse Infrastructure as a Code & Scripting - Terraform or Ansible - Shell Scripting and Python, Pwer Shell, Power Cli Public Cloud IaaS and Associated PaaS - AWS / Azure/ GCP - S3, Blobs, VPCs, vNet, LBs Cloud Watch, Stack Driver, Azure Mon Cloud Native and Containers - PODMAN, Docker Openshift and AKS and GKE and EKE Database Systems (RDBMS, No SQl and Cloud DB) - Orcle and MS SQL or MySQL and Mongo or Couch - Cloud DB (Redis or Aurora, Sql online Midleware (WebServers, Message Qs, Managed Apps, MFT, Job Schedulers - IIS, Apache, JBOSS, WebSphere/ Web Logic MFTs, MQ Series, Control M or Autosys or TWS and MTFs Resource needs to be AI Ready.