Vetted PostgreSQL Professionals

“Backend engineer specializing in event-driven/serverless systems and Python/FastAPI APIs. Built a scalable PDF-to-structured-data pipeline on AWS (S3, Lambda, Step Functions, Textract, DynamoDB, SNS) with strong observability (p50/p90/p99) and reliability patterns (idempotency, retries/DLQs), and has led zero-downtime migrations using feature flags, dual writes, and incremental rollouts.”

“Full-stack engineer with deep ad-tech/marketing automation experience, building production tools that reduce programmatic ad waste and improve search ads performance. Shipped and operated AWS-deployed, Dockerized systems with Postgres/Redis and strong observability (Datadog/OpenTelemetry), and delivered measurable impact (25k campaigns processed, 50k sites negated, 3–4 hours/week saved). Built scalable abstractions for multi-platform ad integrations, enabling rapid onboarding of additional clients.”

“Robotics competition (ABU Robocon) team member who programmed two robots for a rugby-style game, integrating IoT sensors and real-time decision-making. Implemented low-latency, secure inter-robot communication by moving from Bluetooth to ESP8266/NodeMCU WiFi (with Bluetooth as backup) and used OpenCV plus CNN training workflows for vision-related tasks; no practical ROS/ROS2 experience.”

“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”

“Software engineering intern at the Florida Department of Transportation who built validation/anomaly-detection logic for a live operational telemetry + system log processing pipeline. Emphasizes fault-tolerant, state-driven system design (degraded modes, data freshness tracking, safe fallbacks) and debugs time-sensitive behavior via logging/latency analysis and replay-based testing—skills that translate well to robotics-style architectures despite no direct ROS/robot experience.”

“Built a real-time AI meeting assistant using a Chrome extension that streams audio to a backend LLM workflow with transcription and RAG, then hardened it for production with queue-based streaming, async pipelines, security controls, and full observability. Also has hands-on startup sales experience, partnering with customers to define measurable technical win conditions (latency/accuracy) to close deals and drive adoption.”

“Data-driven growth and partnerships professional with experience leading an analytics/reporting vendor rollout end-to-end (vendor selection via stakeholder interviews and PoC, then negotiating scope/pricing/support and tracking adoption/efficiency/accuracy KPIs). At PC Financial, built regression and segmentation models to optimize multi-channel targeting (in-app/email/push), driving +15% campaign engagement and +10% PC Optimum offer loads, and ran behavior-triggered lifecycle experiments that lifted upsell conversion by 20%.”

“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”

“Senior frontend developer with end-to-end ownership of modernizing a legacy Laravel/PHP product into a Next.js 14 + React + TypeScript stack, using TurboRepo for incremental integration. Emphasizes quality and scale through unit testing, Datadog monitoring, and performance-focused UI work (dashboards with charts/usage analytics, minimizing re-renders).”

“Full-stack engineer who built a real-estate professional marketplace platform (Maison) end-to-end as the sole engineer, including a multi-portal Next.js/React architecture, real-time WebSocket collaboration, Prisma/Postgres data modeling, and Stripe subscription billing. Also modernized a government disability case-management system from legacy VB.NET to an Angular + Spring Boot web app, citing measurable performance and workflow improvements.”

“Frontend engineer who led an end-to-end dashboard web app build, starting from UI sketches and user stories through design documentation and a proof-of-concept to align stakeholders. Uses a modern React/TypeScript stack (TanStack Query/Table/Form, shadcn/ui, Tailwind) with Zod validation, ESLint + CodeRabbit PR checks, and Vercel Analytics for performance monitoring.”

“Frontend engineer who has led customer-facing React + TypeScript products end-to-end, building complex dashboards with robust async state patterns (caching, deduping, cancellation, optimistic updates) and strong quality practices (TypeScript standards, layered testing, production monitoring). Experienced modernizing inherited codebases through modularization and performance work (code splitting/memoization) while aligning stakeholders and shipping safely via feature flags and staged rollouts.”

“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”

“Frontend engineer who led end-to-end delivery of a financial data grid and optimized it to handle millions of rows using batching and progressive rendering. Experienced modernizing legacy Razor UIs into maintainable React + TypeScript implementations, leveraging React Query and Jotai, and shipping via incremental builds and feature toggles with close QA/client collaboration.”

“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”

“Recent research master’s graduate who built a Python backend for an interconnected RabbitMQ/MQTT system, including automation, benchmarking, and network-link optimization between brokers. Has hands-on edge computing experience (lightweight Kubernetes on a ~40 Raspberry Pi IoT cluster) and made architecture decisions for real-time streaming by evaluating Kafka and ultimately choosing Apache Storm.”

“Full-stack engineer from Clairvoyant who led end-to-end delivery of a cloud-native, event-driven platform: Spring Boot microservices + Kafka real-time streams with an Angular UI, migrated and containerized on AWS, and automated CI/CD with Jenkins/Maven/Git. Demonstrates depth in distributed consistency challenges (partitioning, consumer lag/duplicates) and database performance tuning across SQL/NoSQL under heavy workloads.”

“Startup-focused builder who created and iterated an MVP for Enky, a two-sided marketplace connecting music artists and creators, informed by hundreds of customer interviews. Implemented CI/CD, monitoring (PostHog/Sentry), and a complex payout pipeline involving scraping social platforms and routing escrow payments via Stripe, and has a track record of quickly debugging production issues (e.g., iOS-specific OAuth cookie failures).”

“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”

“Full-stack engineer with fintech payments experience who shipped an end-to-end guest invoice payment flow emphasizing reliability under retries/failures (idempotency via DynamoDB, async processing with Lambda/EventBridge/SQS + DLQ). Also built a FastAPI backend with Cognito/JWT + scoped guest tokens and a polished React/TypeScript checkout UX, and has performance-focused Postgres/Redis design experience for flash-sale e-commerce workloads.”

“Startup-style full-stack/backend engineer with hands-on AWS architecture experience who shipped an LLM-driven assessment-question automation feature (Python microservice calling AWS Bedrock via SQS, deployed on Lambda) with strong validation/guardrails and retry strategies. Also improved production scalability by moving a CPU/IO-heavy file upload path out of a Go API into a queue/Lambda design monitored with CloudWatch, and has React+TypeScript experience optimizing analytics dashboards.”

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”

“Backend/AI engineer in construction tech (HyperWater AI) who delivered major production performance wins (analytics API from ~1 hour to 0.5s) and shipped LLM features for parsing subcontractor manifests into CSI divisions with human-in-the-loop review. Also built a freelance agentic document-verification system using OCR + RAG over pgvector with robust retry/escalation logic and user feedback loops.”