Vetted MySQL Professionals

Anita Bhagashetti

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud microservices

3y exp

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”

Pavan Kalyan Reddy Gunamareddy

Screened

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare

TX, USA4y exp

“Backend/platform engineer in fintech/payments (NexaBank/NextBank/Nexon Bank) who has built Kafka-orchestrated Java/Spring Boot microservices around a PostgreSQL double-entry ledger. Led production-critical reliability work preventing duplicate payment postings via idempotency and offset sequencing fixes, and shipped real-time ML fraud scoring (Python model API + Redis caching) with rigorous evaluation/monitoring (Prometheus) and workflow automation for dispute resolution.”

hetvi patel

Screened

Mid-level Software/Data Engineer specializing in cloud ETL pipelines and data infrastructure

New Jersey5y exp

“Backend/data engineer who built a production analytics data service (Python/FastAPI on AWS/Postgres with PySpark ETL) handling millions of records per day and drove major latency improvements (10–15s to <2s) via indexing, Redis caching, and shifting aggregations into ETL. Also shipped an LLM-based natural-language-to-SQL assistant end-to-end with strong guardrails (schema restrictions, read-only validation, RBAC, masking) and designed a multi-step agent workflow with verification and fallback logic.”

Md Abul Kalam Azad

Screened

Director-level Software Development Leader specializing in FinTech, Blockchain, and AI

Kuala Lumpur, Malaysia24y exp

“Bootstrapped founder with a technical background who has already built an MVP SaaS loyalty and referral platform plus a tablet/mobile POS companion product, leveraging Azure and Google Cloud support rather than outside capital. Focused on learning-by-building, resource-efficient execution, and forming highly motivated, equity-aligned teams.”

Jayanth Amol Ergola

Screened

Mid-Level Software Engineer specializing in full-stack development and data engineering

Milpitas, California4y exp

“Backend engineer with production experience at KeyBank building high-volume Java/Spring Boot services on Azure with PostgreSQL/Oracle, including async job ingestion and tracking. Demonstrates strong reliability/performance debugging (HikariCP pool exhaustion, DB contention) and has shipped an LLM-powered data analysis/summarization feature with robust production guardrails (validation, shadow testing, deterministic fallbacks, audit logs).”

“Data engineer who has owned high-volume production pipelines end-to-end (200–300 GB/day) on AWS, implementing strong data quality/observability and achieving 99.9% reliability while cutting data issues ~33%. Also built a large-scale external data collection system ingesting millions of records/day with anti-bot/rate-limit handling and backfill tooling, and shipped a versioned REST service exposing curated Snowflake data to downstream teams.”

“Built and shipped a personal LLM-powered news aggregation platform (Clear Brief) that scrapes ~200 articles per cycle, clusters them into ~15–30 consolidated stories, and supports on-demand deep dives via a Next.js API route. Emphasizes production-minded reliability (token/cost controls, timeouts, graceful frontend degradation) and database-backed orchestration using SQLite with retry + exponential backoff for burst processing.”

“Bootstrapped founder of FAMRO LLC with 15+ years spanning startups and corporate roles, including COO experience at an AI/ML startup that built a retail marketing analytics product using camera feeds. Also worked on a clean-tech venture, EnerIO, which won 1st position from Pakistan and was invited to pitch at the GCIP/GEF event in San Francisco in 2015.”

“Engineer with hands-on experience building adaptive assessment and LMS-style platforms across React/TypeScript, edge/serverless backends, and Postgres, with strong evidence of cross-layer debugging and performance optimization. Also brings ML product experience from a small-team internship, where they shipped a CatBoost-powered investor demo under ambiguity and created reusable inference infrastructure.”

“Analytics-focused candidate with hands-on experience building SQL and Python pipelines for messy, high-volume data across e-commerce, marketing, healthcare, and regional resource allocation use cases. Particularly strong in turning ambiguous business problems into operational metrics and trusted Power BI reporting, including CLV, patient retention, and vulnerability-based segmentation.”

“Junior web developer turned applied AI builder who has shipped both user-facing web UX improvements (Vue.js + Drupal/Twig) and production LLM systems. Built a Google Cloud-hosted Llama/Ollama RAG customer-service chatbot with citation-based guardrails and a metrics-driven eval loop, and also delivered a large-scale Python pipeline analyzing 14M Amazon consumer reviews for flavor-trend detection.”

“Full-stack product engineer who led system design and backend/cloud architecture for a senior-living platform spanning an Android kiosk and admin web portal. They combine Azure microservices expertise with strong accessibility instincts, and their UI/UX improvements for seniors and wheelchair users reportedly helped drive 21% revenue growth and a new customer through word of mouth.”

“Analytics-focused candidate with hands-on experience building compliance and contract utilization reporting from messy contract, vendor, subcontractor, and payment data. They combine SQL and Python automation to improve reporting speed and accuracy, and show strong stakeholder discipline through validation sessions, documentation, and dashboard adoption.”

“Built and owned enterprise data/integration deployments and production AI workflows, including a Python-based migration pipeline that moved 2M records with major improvements in onboarding speed, error rate, latency, and uptime. Also shipped a financial RAG assistant over 50K documents with sub-second p95 latency, showing a strong blend of customer-facing deployment ownership, data engineering, and LLM systems expertise.”

“Built production LLM-powered mobile apps using OpenAI APIs on a serverless Firebase/Google Cloud Run stack, including a prayer app serving global users across five major religions with customized prayer generation. Stands out for adding reconciliation and scoring layers to validate non-deterministic AI outputs before showing them to users, and for iterating prompts based on logged failure patterns.”