Software Engineer @ ServiceSphere UG ( Backend Engineering | Distributed Systems | Cloud Native Systems | AI )

Building scalable backend systems, distributed architectures, and cloud native applications using Python, PostgreSQL, Kafka, Redis, AWS, and Azure.

• Backend Software Engineer with 2+ years of experience
• Building scalable backend systems using Python, Django, FastAPI, and PostgreSQL
• Interested in Distributed Systems, System Design, Cloud Native Applications, and AI powered Platforms
• AWS Certified Cloud Practitioner
• Microsoft Certified Azure Fundamentals

• Building distributed systems and event driven architectures
• Deepening expertise in system design and scalability
• Exploring Go for high performance backend services
• Preparing for product engineering and FAANG level interviews

Python • Django • FastAPI • PostgreSQL • Redis • Kafka • AWS • Azure • Docker • Kubernetes

Event driven notification platform built using FastAPI, Kafka, Redis, PostgreSQL, Prometheus, Grafana, Docker, and Kubernetes with support for asynchronous processing, retry mechanisms, DLQ handling, rate limiting, and observability.

Production grade backend platform connecting customers with verified service providers through quotation, booking, and service management workflows using Django, PostgreSQL, AWS, and AI powered voice to text and renovation preview capabilities.

Enterprise administration platform developed to manage provider onboarding, account verification, service configuration, revenue tracking, workflow governance, and operational oversight through secure REST APIs and role based access control.

Multimodal AI platform that transforms recorded conversations into transcripts, emotion insights, delivery analysis, and conversation intelligence using SpeechBrain, Wav2Vec2, PyTorch, and LLM powered processing.

RAG powered semantic search system using LangChain, OpenAI Embeddings, FAISS, and retrieval pipelines to enable intelligent document search, summarization, and question answering across unstructured content.

End to end MLOps workflow built using Azure ML, AKS, Azure Pipelines, Flask, and Python to automate model deployment, CI/CD, and scalable cloud native inference.

• Advanced System Design
• Distributed Systems
• Go
• High Scale Backend Architecture

• Microsoft Certified: Azure Fundamentals (AZ-900)
• AWS Certified Cloud Practitioner (CLF-C02)

• LinkedIn: https://linkedin.com/in/saif-mansoor
• GitHub: https://github.com/sayfxmansoor019