Vetted JSON Professionals

“Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.”

“Frontend engineer who has led enterprise-scale UI delivery end-to-end on a microservices platform, designing modular Angular SPAs (v12-17) tightly aligned to Spring Boot REST APIs. Emphasizes quality and release velocity through layered testing (Karma/Jasmine), CI/CD automation (Jenkins/Azure DevOps), performance tuning with RxJS/lazy loading, and incremental rollouts with close product/design/QA collaboration.”

“Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.”

“Frontend-focused engineer who has led end-to-end delivery for an ecommerce web app and built complex React + TypeScript dashboards with real-time data and multi-step workflows. Strong in scalable architecture (typed API layers, shared hooks, design systems), quality at scale (Jest/RTL + Playwright), and performance optimization (virtualization, lazy-loading, memoization). Experienced shipping high-impact checkout changes via feature-flagged rollouts with metric/error monitoring and rapid iteration.”

“Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.”

“Robotics/AI Master's thesis researcher building an LLM-driven workflow to generate and evaluate robot policies before running them in an environment. Also built a local LLM-based real-time target-tracking robot using a pan-tilt camera with LangChain + Ollama, and has hands-on ROS 2/Gazebo experience including URDF-based simulation and a TurtleBot multi-agent chase project.”

“Built and productionized a GenAI prompt-engineering solution to retrieve prevailing wages based on job/location selections, emphasizing accuracy through stricter prompt templates and validation. Hands-on in real-time production debugging using Splunk (callback tracing, verbose logging, header inspection) and experienced running developer-facing demos/workshops that helped drive marketplace API adoption.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“Built and shipped multiple production LLM/agentic systems, including an agentic RAG NL-to-SQL analytics app that cut manual reporting from 9 hours/week to 15 minutes by grounding on schema-aware retrieval and robust fallback/monitoring. Also implemented a LangChain supervisor-orchestrated enterprise IT automation agent that routes requests for search, identity validation, and action execution, and created a RAG search tool spanning Jira/Confluence/SharePoint for operations stakeholders.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Built and deployed a production LLM-powered text extraction/classification system that converts messy unstructured reports into searchable insights, running on AWS SageMaker with automated retraining and monitoring. Strong in orchestration (Step Functions/Kubernetes/Airflow patterns) and reliability practices (gold datasets, prompt/tool unit tests, shadow/canary/A-B testing, guardrails/rollback), and has experience translating non-technical stakeholder needs into an NLP workflow plus dashboard.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“Backend engineer with recent Barclays experience building a Python asyncio + Kafka risk reporting service for trading desks, including a major refactor from blocking batch processing to event-driven incremental pipelines to restore intraday/EOD performance. Also shipped an applied AI feature using OpenAI fine-tuning to classify risk-breach severity and generate trader/risk-manager summaries with robust retry/fallback handling, plus demonstrated strong database/query optimization (triggers, materialized views, partial indexes) in a risk-limits/breaches domain.”

“AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.”

“Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.”

“Software engineer with payments-domain experience (Visa) building real-time transaction monitoring and analytics systems. Strong end-to-end ownership across Spring Boot/Kafka microservices, PostgreSQL modeling, and AWS/Kubernetes operations, plus React+TypeScript dashboards—focused on low-latency processing, secure APIs, and zero-downtime production releases.”

“Full-stack engineer who built and supported production features in a productivity/task-tracking app using Next.js App Router + TypeScript (server components for initial render, client components for interactivity, API route handlers for mutations). Also designed and optimized Postgres data models/queries and implemented resilient, event-driven payment processing with idempotency, retries, audit logs, and strong testing/observability practices.”

“Insurtech R&D leader turned CTO with 25+ years across telecom, DoD, automotive, and commercial insurance. Built patented AI-driven insurance document ingestion (>95% accuracy with 1–3 samples) and led Azure-based backend/service development while managing up to 15 engineers at a commercial P&C MGA that reached a ~$60M book of business (~30 loss ratio) before run-off due to paper issues. Known for hands-on discovery (including field inspections) and rapid MVP delivery, including a risk-inspection iPad app that auto-generated draft reports.”

“Open-source JavaScript contributor focused on data visualization, extending Chart.js/React with custom plugins for real-time streaming dashboards. Designed an end-to-end telemetry pipeline using Apache Kafka and Azure Cosmos DB, optimizing partitioning, batching, caching, and client throttling to keep latency low and support thousands of concurrent users. Demonstrates strong ownership in fast-changing environments, including building full-stack AI applications and ingestion/ETL pipelines at Robotics Technologies LLC.”

“Full-stack engineer focused on enterprise, cloud-native microservices—building Spring Boot backends and React/Angular front ends with strong security (OAuth/JWT), AWS infrastructure (RDS/S3), and containerized deployments (Docker/Kubernetes). Has delivered data-heavy order/account/transaction platforms and healthcare solutions including EHR integrations for secure patient data exchange, with emphasis on testing, performance tuning, and reliability (load testing).”

“Built a production AI-driven contract/document extraction system combining OCR, normalization, and LLM schema-guided extraction, orchestrated with PySpark and Azure Data Factory and loaded into PostgreSQL for analytics. Emphasizes reliability at scale—using strict JSON schemas, confidence scoring, targeted retries, and multi-layer validation to control hallucinations while processing thousands of PDFs per hour—and partners closely with non-technical business teams to refine fields and deliver usable dashboards.”

“Backend engineer with hands-on experience building secure Python/Flask services (sessions, JWT, RBAC) and optimizing PostgreSQL/SQLAlchemy performance, including custom SQL using CTEs/window functions profiled via EXPLAIN ANALYZE. Also integrates LLM features via OpenAI/Azure into backend systems and improves scalability with RabbitMQ-driven async processing, caching, and multi-tenant data isolation patterns.”