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 : Platform as a Service Providers (PaaS)
Good to have skills : NA
Minimum 5 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
AI Powered Tech Talent
The Cognitive PaaS Full Stack Engineer designs and develops cognitive cloud applications and services-ranging 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.
- Bachelor s or Master s 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)
- Resource needs to be AI Ready.