Vetted Microsoft Azure Professionals

Maheswari Thokala

Screened

Mid-level Full-Stack Engineer specializing in cloud microservices and REST APIs

CA, USA4y exp

“Backend engineer building an AI-powered social media platform on AWS, with hands-on experience shipping LLM-backed application features and improving production performance under high traffic. Strong focus on reliability/observability (CloudWatch, structured logs, health checks) and database optimization (MongoDB explain/slow logs, indexing, caching, connection pooling).”

“Internship-built full-stack systems spanning HR employee-record portals and internal data-quality dashboards (Flask + SQL + React), emphasizing data integrity and rapid MVP iteration. Also implemented Flask microservices with RabbitMQ for distributed task processing, addressing duplication/ordering issues with idempotency, durable queues, and correlation-ID logging; delivered quantified productivity gains for HR teams.”

“Frontend engineer with strong experience building enterprise-grade banking interfaces, including a cross-platform credit card application with secure document uploads, real-time status tracking, and complex multi-step e-forms. Stands out for combining React/TypeScript architecture skills with deep browser-level debugging and measurable UX improvements in regulated financial environments.”

Ahmad Rayyan

Screened

Entry-level Full-Stack Engineer specializing in Applied AI and multi-agent systems

Pakistan1y exp

“Built both traditional full-stack products and advanced LLM systems, from a React/Flask dashboard used by instructors to monitor GitHub contribution patterns to multi-agent benchmark infrastructure at Analytiverse. Particularly strong in evaluation-heavy AI engineering: designed executable verifiers, force-zero anti-reward-hacking checks, and token-optimization strategies that delivered a 40-point pass-rate lift and 90x token reduction on SwarnBench tasks.”

“Early-stage product engineer who built an AI persona chat system end to end at Super Intro, spanning Next.js frontend, GraphQL/real-time backend, retrieval memory, and LLM-based matching. They combine strong TypeScript rigor with practical AI systems design, and cite measurable impact including ~40% engagement growth, ~30% recall improvement, and lower LLM costs in production.”

“Python backend developer from Larix Technologies who built and scaled microservice APIs for an omnichannel messaging SaaS (WhatsApp/Instagram/Facebook) and led production performance fixes during peak traffic, cutting webhook latency ~50%. Also shipped applied AI products end-to-end: a RAG-based PDF assistant (LangChain + Mixtral via Groq + React) and a BI agent that plans/executes/verifies multi-step analytics with strong guardrails and auditability.”

“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”