Vetted Load Balancing Professionals

“Built and productionized an LLM-based appointment management agent, implementing RAG with Redis and LangGraph plus multi-agent intent handling and rule-based conflict guardrails to prevent double-booking under high load. Experienced in real-time diagnosis of agentic workflow failures using logs/traces and state inspection, and in driving adoption via interactive developer demos and sales-aligned custom customer scenarios.”

“Backend engineer who evolved and migrated a real-time smartwatch telemetry ingestion/analytics platform in a healthcare context, focusing on reliability under poor network conditions. Experienced with Python/FastAPI and Java microservices, PostgreSQL performance tuning, and production-grade security (JWT/OAuth, RBAC, RLS) with incremental rollout and parallel-run migration strategies.”

“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.”

“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 who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Built and deployed a production RAG-based multilingual analytics assistant for healthcare operations, enabling non-technical teams to query claims/EHR and risk metrics with grounded explanations. Demonstrates strong end-to-end LLM system engineering (retrieval tuning, re-ranking, hallucination controls, verification layers) plus workflow orchestration (Airflow/Composer/Step Functions) and stakeholder-driven iteration via prototypes and dashboards.”

“Frontend engineer who created an in-house React-like framework (“React-Wilcox”) enabling modern, event-driven UI components on extremely legacy browsers (as far back as 2002), including race-condition avoidance via batched state updates. Also does freelance work untangling AI/vibe-coded frontends for nontechnical founders, componentizing UIs and fixing routing/readability, and recently built a React+TS social app for martial artists with privacy-preserving location distance features.”

“Frontend engineer with React/TypeScript experience who has led end-to-end UI work on a fintech product (React frontend with NestJS APIs), emphasizing performance (virtualized rendering, memoization, lazy loading, profiling) and quality at scale (unit tests and TDD). Also built and iterated on a snooker sports app, simplifying UX through audience-focused design decisions and streamlined onboarding.”

“LLM/agent systems builder who deployed a production hybrid router for immerso.ai that dynamically selects retrieval vs reasoning vs generative pathways, achieving an 82% factual-accuracy lift. Deep hands-on experience optimizing local Mistral 7B inference (4–5 bit GGUF quantization, KV-cache reuse) and building reliable RAG/agent workflows with LangChain/LangGraph/AutoGen across GCP Cloud Run and AWS (ECS/Lambda).”

“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”

“Software engineer with experience across edtech, live gaming, and an AI document intelligence platform, delivering end-to-end customer-facing features and production backends. Built secure, automated live-session scheduling integrating Zoom and TalentLMS (JWT/RBAC, idempotency, transactions) cutting setup time from ~3 minutes to under 1 minute, and optimized real-time gaming dashboards/APIs with query tuning, caching, and CDN improvements (~60% latency reduction under peak load) on AWS.”

“Data engineer with experience at Morgan Stanley and Star Health owning production-grade lakehouse pipelines for credit risk and healthcare datasets. Built Azure/Databricks/Delta/Snowflake-based platforms processing millions of records per day with strong data quality, observability (Monte Carlo/Azure Monitor), and reliability practices, plus experience delivering curated data services with performance tuning and backward-compatible versioning.”

“Unity developer focused on VR/AR multiplayer, with hands-on experience building Photon Fusion/PUN systems including networking, sync, and matchmaking. Has scaled a modular multiplayer architecture to handle more players/features while addressing latency and data consistency, and has optimized Meta Quest/mobile performance using pooling, LODs, batching, and profiling.”

“Unity game developer with hands-on gameplay AI experience (FSM-driven monsters with customized NavMeshAgent movement) focused on creating readable, high-tension survival encounters through iterative tuning. Has shipped/created 4 Unity games solo end-to-end (UI, animations, architecture, state machines) and has also built a full Python game server; some exposure to Photon Fusion and strong client/server REST API implementation experience.”

“Owned and stabilized Decathlon e-commerce payment services, taking a prototype reliability effort to production by implementing failure detection/retries, load testing, and DB performance optimizations—reducing payment failures and cart abandonment. Also demonstrates an LLM/agentic workflow support mindset with strong observability, rapid incident diagnosis, and durable prevention via RCA, safeguards, and regression/replay testing, plus experience supporting sales/support with technical reassurance.”

“Software engineer with experience spanning healthcare middleware (patient records + insurance integration) and an AI fantasy football product built with React/TypeScript, Firebase, API gateways, and pandas-based data pipelines. Has hands-on microservices scaling experience (latency mitigation, async migration, state-based redesign) and built an internal feature-toggle dashboard that improved demo efficiency and sales outcomes.”

“Full-stack engineer with strong production experience improving performance and reliability of data-heavy analytics products. Has shipped end-to-end features spanning Node/Express + PostgreSQL + Redis and React/TypeScript, deployed via Docker/GitHub Actions to AWS EKS with Helm, and monitored with Datadog/CloudWatch; also built a Python compliance automation backend for AWS security monitoring with RBAC, versioned REST APIs, and resilient throttling-aware processing.”

“Internship project building and deploying a LLaMA-based, RAG-enabled copilot inside a Professional Services Automation platform, enabling natural-language navigation, text-to-SQL reporting, and project/resource/budget insights across multiple modules. Addressed real production issues like context drift and vague queries with hybrid search, metadata enrichment, and an intent classification/rewriting layer, orchestrated via Apache Airflow—ultimately cutting PMO reporting time by 40%.”

“Software engineer (Lance Soft Engineering) who built a Java/gRPC real-time request tracking system supporting ~20K simultaneous requests, using Kafka event streaming and PostgreSQL to improve transparency and cut support requests by 35%. Demonstrates strong production operations skills—resolved live latency spikes with Kafka async messaging (+48% throughput) and executed safe migrations using parallel runs, staging validation, and blue-green deployments.”