Mahammad Iqbal Shaik
Senior Ai Engineer @Right Skale, Inc
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WORK HISTORY
Senior Ai Engineer @Right Skale, Inc
Pleasanton, CA, US
Developed RESTful APIs for enterprise RAG platform handle 100K+ queries/month, enabling multi-tenant document management, semantic search, and conversational interfaces with source citation.Architected event-driven asynchronous document ingestion pipeline using Amazon SQS to decouple parsing, classification, and embedding microservices, processing 10K+ documents/day across 50+ enterprise tenants with isolated failure handling.Built reliable multi-tenant authentication service leveraging Firebase Admin SDK, and custom JWT implementation to provide isolated user pools, tenant-specific claims, and flexible token management, securing 50+ B2B SaaS clients with zero security incidents.Improved RAG answer quality by 20% by implementing distributed tracing with LangFuse, linking ingestion traces to query failures, enabling a root-cause analysis and data-driven chunking optimizations.Implemented tenant-isolated monitoring with granular cost attribution and dedicated debugging views for customer-specific issues, tracing per-tenant API usage (OpenAI, Cohere, Vector DBs).
EDUCATION
Jawaharlal Nehru Technological University, Kakinada
Bachelor of Technology - BTech, Computer Science
University at Buffalo
Masters, Computer Science
ABOUT MAHAMMAD IQBAL SHAIK
I\'m a software engineer (AI / ML) with 5+ years building production microservices and distributed systems that bridge cutting-edge AI with enterprise reliability. Currently architecting multi-tenant RAG platforms using event-driven microservices (SQS) with clean separation of concerns, comprehensive observability (LangFuse, distributed tracing), and secure multi-tenant isolation (JWT, OAuth2.0). Previously reduced ML feedback loops from days to hours for 150K+ schools while maintaining strict SLAs.Deep expertise in modern software engineering practices: designing RESTful/gRPC APIs following SOLID principles, implementing Saga patterns for distributed transactions, containerizing with Docker/Kubernetes, and ensuring reliability through CI/CD pipelines with integration testing (Testcontainers, WireMock). Proven track record optimizing system performance: from Redis caching strategies that cut API latency to building hybrid ML pipelines that reduced OCR errors by 40%.Strong foundation in AI/ML (LLMs, RAG, DPO fine-tuning) paired with systems engineering depth (built Kafka wire-protocol and Redis Server from scratch). Masters in AI from SUNY Buffalo (3.97 GPA). Known for writing clean, testable code that scales. I have proven record of implementing ETL pipelines with automated quality checks, building semantic search services, or developing Spring Boot/FastAPI microservices that handle millions of requests.Key improvements:Microservices architecture - Event-driven, SQS decoupling, service isolationEngineering practices - SOLID principles, Saga pattern, clean interfacesTesting & reliability - CI/CD, integration testing tools explicitly mentionedCode quality signals -\"Clean, testable code,\" OOP principles, separation of concernsPerformance engineering - Caching, optimization, handling scale
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