Infrastructure Technical Support Practitioner and Cognitive PaaS Full Stack Engineer

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 : Platform Engineering
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Cognitive PaaS Full Stack Engineer

Summary
The Cognitive PaaS Full Stack Engineer designs and develops cognitive cloud applications and services anging from user interfaces to API layers and AI integration middleware. The engineer works across front-end, back-end, and cloud infrastructure layers to deliver intelligent, data-driven solutions that leverage AI/ML models, agentic workflows, and cognitive automation frameworks.

Key Responsibilities:
- Design, develop, and maintain end-to-end cognitive PaaS applications 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.
- 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.
- Knowledge of Application Architecture Microservices vs Event Driven Architecture Vs Cloud Based Architecture Vs Cloud native architecture
- Good experience in application modernization support, deploy, manage and maintain cloud native applications on Paas/ Cloud Native Architecture
- Cloud Data Security knowledge and experience in implementing Data Security practices
- 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:
- Strong proficiency in cloud platforms - AWS, Azure, and Google Cloud.
- Bachelors or Masters degree in Computer Science, Software Engineering, or related field.
- Strong in JavaScript (React, Node.js) and Python (Flask, FastAPI) development.
- Experience developing and deploying cognitive or AI-driven microservices.
- Proficiency in cloud platforms (AWS Lambda, Azure Cognitive Services, or Google Vertex AI).
- Familiarity with platform engineering principles API management, service mesh, observability, and IaC (Terraform, Ansible).
- Understanding of NLP, LLM integration, and generative AI architectures for PaaS environments.
- Hands-on experience with DevOps practices CI/CD pipelines, version control (Git), and container orchestration.
- Experience with security frameworks including OAuth2, JWT, and RBAC for multi-tenant systems.

Certifications (Required / Preferred):
- AWS Certified Solutions Architect Professional
- Microsoft Certified: Azure Solutions Architect Expert
- Google Professional Cloud Architect
- Certified Kubernetes Administrator (CKA)
- HashiCorp Certified: Terraform Associate
- Certified DevOps Engineer certifications (AWS, Azure, or Google)
- Resource needs to be AI Ready