Vetted Amazon RDS Professionals

“Software engineer with demonstrated production performance wins (37% latency reduction) through SQL optimization, backend API redesign, and disciplined rollout practices (staging, feature flags). Experienced debugging distributed pipeline issues across infrastructure layers (memory pressure and network timeouts) and building AWS-based systems (Lambda + RDS) to handle request spikes, including work on a business-focused chatbot.”

“Built a voice-driven desktop assistant for users with mobility impairments, integrating Whisper and Google Gemini and adding voice-authentication via speaker embeddings for secure command execution. Has hands-on experience with AWS serverless/microservices patterns (Lambda, S3, CloudFront, CloudWatch) and CI/CD, plus built an internal MySQL-to-MongoDB migration tool used by the CTO and dev team with an emphasis on safe, low-impact data transformation.”

“Full-stack developer who owned and shipped an end-to-end web application for LeafNBeyond (React/Node/Postgres), deployed to production at leafnbeyond.com, with reported 35% sales growth and strong UX feedback. Also built Azure-based ETL pipelines using lakehouse/medallion architecture with validation and retry logic, and has AWS fundamentals from a master’s coursework (EC2, RDS, IAM, load balancing).”

“Builder with hands-on experience shipping full-stack products across AWS cloud infrastructure, React/TypeScript apps, SQL-backed systems, and privacy-focused AI workflows. Stands out for combining cost-aware architecture, strong debugging instincts, and product thinking—from an e-commerce platform automated with IaC to a university admin portal serving 10,000+ users and a locally run AI assistant with configurable guardrails.”

“AI/LLM engineer with production experience delivering large-scale RAG and voice-agent solutions for banking clients. Implemented a SharePoint-based, non-technical content update workflow with incremental hourly ingestion into a vector DB, and actively contributes to Microsoft’s open-source GPT-RAG accelerator while using modern orchestration (Semantic Kernel, LangGraph) and LLM observability/evaluation tooling.”

“Built and shipped production LLM-driven pipelines for clinical data processing, turning semi-structured inputs into validated structured outputs for downstream analytics. Emphasizes predictability and safety via strict JSON schemas, state-machine orchestration, backend-controlled tool calling, and robust fallbacks (rule-based checks/manual review) plus monitoring and offline/online evaluation loops; also has experience hardening workflows against messy ERP/finance data with idempotency and state tracking.”

“Built and shipped a production AI assistant for a web-based loan/interest calculator that helped users understand EMI results and optimize inputs. Demonstrated full-stack ownership across responsive UI, Node.js APIs, and LLM integration, with a strong focus on prompt refinement, guardrails, caching, fallbacks, and post-launch iteration driven by logs and user behavior.”

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).”