Vetted JWT Professionals

“Backend engineer at Discover who built and scaled Python/Flask services for a card dispute resolution platform, tackling long-running external network validations with Celery+Redis and delivering measurable gains (response time ~3s to <300ms; throughput +40%). Experienced in high-scale PostgreSQL/SQLAlchemy optimization (partitioning, read replicas, N+1 avoidance), event-driven systems with Kafka, and integrating ML fraud detection using AWS SageMaker/Lambda/ECS with clear separation of real-time vs batch processing.”

“Backend/platform engineer who owns policy-lifecycle workflow microservices built in Python/FastAPI with async + DDD, Kafka event processing, SQLAlchemy, JWT/RBAC, and Redis caching (cut DB load ~40%). Experienced deploying Java and Python microservices to Kubernetes with Helm and GitOps (ArgoCD) plus Jenkins/GitHub Actions pipelines to AWS/ECR, and has supported phased on-prem-to-cloud migrations with dependency mapping and data consistency strategies.”

“Backend engineer focused on cloud analytics/cost-optimization systems, with strong AWS-centric architecture experience (serverless Lambda, ECS, CloudWatch). Demonstrated deep PostgreSQL/SQLAlchemy optimization at million-record scale (including JSONB/GIN indexing) and built production ML inference services with S3-based model versioning and Airflow retraining pipelines. Also has hands-on multi-tenant SaaS design (separate schemas + RLS) and high-throughput background processing using Celery/Redis with measurable performance gains.”

“Built an AI lending assistant (RAG + DeBERTa) used by credit analysts to retrieve policies and past loan decisions, tackling real production issues like hallucinations, document quality, and sub-second latency. Deployed a modular, Dockerized AWS architecture (ECS/EMR + load balancer) with load testing, caching/precomputed embeddings, and CloudWatch monitoring, and used Airflow to automate scheduled data/embedding/vector DB refresh pipelines with retries and alerts.”

“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”

“Full-stack engineer with hands-on ownership of a real-time loyalty rewards notification system at Dell, spanning React UI, Spring Boot/Node microservices, Kafka event processing, and Oracle/Postgres persistence. Strong production operations experience across AKS/Azure DevOps and AWS (EC2/RDS/S3, autoscaling, CloudWatch), including resolving peak-load Kafka lag and API latency incidents through scaling and performance tuning.”

“Full-stack engineer with strong production ownership in banking/identity & entitlements systems, building Spring Boot + Postgres/Redis services and React dashboards, then deploying on AWS EKS with Jenkins CI/CD. Demonstrated impact through reduced authorization latency and fewer access-related support tickets, plus strong observability and reliability practices (CloudWatch, tracing, autoscaling, Kafka pipelines with DLQs and reconciliation).”

“Full-stack engineer who built a cloud storage app feature (file upload/management) with Next.js App Router + TypeScript and owned post-launch improvements. Also has internship experience building a geospatial AI chatbot: designed Postgres/PostGIS data models and optimized spatial queries, and implemented an LLM workflow orchestrated with LangChain/LangGraph plus a RAG pipeline grounded in OpenStreetMap data to reduce hallucinations.”

“Software engineer with experience building and iterating high-volume Spring Boot microservices on AWS (Docker/Kubernetes) and integrating with React front-ends. Also delivered an LLM-powered document summarization system using embeddings + retrieval (RAG) with grounding/guardrails and built evaluation loops that directly drove retrieval and chunking improvements. Has scaled Kafka-based pipelines processing millions of messy financial/infrastructure records with reliability and cost/latency tradeoff management.”

“Software engineer who built and launched an end-to-end Ad Scheduler that automated campaign creation across Google Ads and Meta using Azure Functions/Service Bus, PostgreSQL, and a React frontend—reducing manual marketing ops work. Also shipped a production internal RAG chatbot leveraging a data warehouse + Cube semantic layer, Gemini embeddings, vector search, and Claude, with Langfuse tracing and brand-based access controls; work was cut short due to layoffs.”

“Backend engineer with deep experience building and evolving financial-services workflow systems where correctness, data integrity, and reliable state transitions outweigh raw throughput. Emphasizes idempotent, contract-driven FastAPI APIs with defense-in-depth security (JWT + row-level security) and careful, low-blast-radius migrations using feature flags, dual writes/shadow reads, and incremental rollout.”

“Backend engineer with healthcare domain experience building AI-driven radiology workflow systems. Evolved tightly coupled APIs into secure, reliable FastAPI-based services by moving heavy imaging/data processing into idempotent asynchronous pipelines with retries, feature-flagged incremental rollout, and strong data-integrity controls (constraints, backfills, validation). Strong focus on defense-in-depth security for sensitive patient data (OAuth2/JWT, RBAC, and database-level protections).”

“Backend engineer who built and launched a warehouse locations/inventory microservice for Walmart, supporting a new product rollout with on-call war-room ownership and now running across all US distribution centers. Emphasizes reliability and correctness (background syncs, 2PC concepts, alerting) plus design-first API development in Python/FastAPI with OAuth/JWT and RBAC, and has led staged legacy-to-microservice migrations with continuous data integrity verification.”

“Backend engineer with hands-on experience modernizing high-volume transactional systems by decomposing monoliths into Spring Boot microservices on AWS, using Kafka for async workflows and Redis/SQL tuning for latency. Has built Python/FastAPI services with strong API contracts and production-grade security (OAuth2/JWT, RBAC, row-level security), and proactively hardened payment flows against race conditions and double-charging via idempotency.”

“Backend/data platform engineer who has built and operated a cloud-native media ingestion/processing platform in Python (Django/DRF, FastAPI) with Kafka, Postgres, and Redis, emphasizing multi-tenant security and reliability. Delivered AWS production systems combining EKS and Lambda with Terraform + GitHub Actions/Helm, and built Glue-based ETL pipelines with strong schema-evolution and data-quality practices; also modernized SAS analytics into Python on AWS. Seeking fully remote roles with a $120K–$140K base range.”

“Backend engineer focused on Node.js (Express/Fastify) and MongoDB who designed a multi-stage bill-approval workflow system for a manufacturing company, emphasizing RBAC, auditability, and scalability across multiple factory units. Also improved system robustness by catching a MongoDB connection leak in an Excise department project and has experience executing low-risk, incremental backend refactors with monitoring and rollback.”

“Built and shipped a production LLM-powered RAG system at Upstart enabling natural-language search across 50k+ scattered internal technical docs. Delivered sub-300ms p95 latency for ~50 active users with strong hallucination safeguards (retrieval-first, thresholds, citations) plus robust testing/monitoring and cost controls (prompt caching cutting API spend ~20%).”

“Entry-level software engineer who built an agentic AI backend in Python/FastAPI, including APIs for conversation history retrieval and user data storage, and worked through async/concurrency challenges for multiple agents querying simultaneously. Also has practical AWS experience using S3 for static hosting with Lambda and RDS for backend/data access.”

“Backend/data platform engineer who owned end-to-end production services for a fleet analytics/GenAI platform, spanning FastAPI microservices on Kubernetes and AWS (EKS + Lambda) event-driven workloads. Strong in reliability/observability (OpenTelemetry, circuit breakers, idempotency), data pipelines (Glue/Airflow/Snowflake), and measurable performance/cost wins (SQL 10s to <800ms P95; ~30% compute cost reduction).”

“Software engineer who built and owned a centralized Asset Management platform at Hyundai Mobis used daily by multiple internal teams, delivering everything from UI/TypeScript React frontend to Spring Boot services, databases, deployment, and post-release support. Experienced in scaling microservices with Kafka-based async workflows, improving data consistency/real-time updates, and implementing reliability patterns like standardized API contracts, retries, DLQs, and targeted caching.”

“Frontend engineer with experience delivering complex, data-heavy React + TypeScript dashboards in financial services (Morgan Stanley), including React 18 migration and rigorous quality practices (~80% test coverage). Also improved an existing collaboration product (Heycollab) by reducing duplication and boosting performance ~30% using component modularization, API optimizations, code splitting, and virtualization; experienced with phased rollouts and feature flags for risk-sensitive releases.”

“Software engineer with deep healthcare claims domain experience who has owned customer-facing portals end-to-end (Java/Spring Boot + React/TypeScript) and improved usability/performance based on real user feedback. Built microservices using REST and RabbitMQ with strong observability (Splunk/cloud metrics), and delivered an internal claims investigation dashboard that streamlined operations through centralized data, search, and filtering.”

“Software engineer experienced owning internal, customer-facing dashboards and internal ops tools end-to-end, emphasizing fast iteration without sacrificing stability (CI/CD, automated tests, feature flags, monitoring). Built a TypeScript/React role-based dashboard backed by Java Spring Boot and has hands-on microservices experience with RabbitMQ, including production hardening with retries, dead-letter queues, logging, and health checks.”

“Robotics software engineer who built the software layer for an autonomous warehouse sorting system, spanning navigation/path planning, task scheduling, and backend services. Deep hands-on ROS 2 Foxy experience (Nav2/costmaps) and real-time multi-robot debugging, using simulation-driven analysis plus incremental/partial re-planning to handle dynamic obstacles in production-like warehouse environments.”