Vetted REST API Professionals

“Backend engineer with insurance/claims domain experience who modernized legacy claims processing systems to support AI-assisted claim review. Emphasizes production-ready API design in Python/FastAPI (schemas, async, caching, graceful degradation), strong observability with Prometheus, and layered security including JWT auth plus database row-level security (Supabase/Postgres).”

“Full-stack + ML engineer who built “Finsight,” a real-time financial risk platform (React/FastAPI/MongoDB/AWS Lambda) processing 2M+ records monthly, using sharding and Redis caching (60% DB load reduction) plus async and batch optimizations. Also has healthcare product experience at Apollo Healthcare, partnering directly with clinicians/admins to design and iterate EHR dashboards via Figma prototyping and user testing, and demonstrates clear system design thinking for real-time voice-to-LLM architectures.”

“Full-stack engineer from Vagaro who owned an end-to-end rebuild of a sluggish WordPress sales site into a Next.js 15 app hosted on Azure, adding Hygraph headless CMS, SSR, i18n, and a reusable component library. Instrumented Amplitude + A/B testing/heatmaps and reports a 10% sales lift post-launch; also has AWS ops experience (S3/IAM/CloudWatch) and has built ingestion pipelines including LLM-powered unstructured data processing with dead-letter handling.”

“Backend engineer with experience in fraud reporting and billing systems, building Java/Spring Boot services behind a React frontend and improving performance 40%+ with caching and SQL optimization while maintaining 99.9% uptime. Has hands-on experience migrating a monolith to microservices with incremental rollout, clear data ownership boundaries, and production-grade API reliability/security practices (JWT/OAuth, RBAC, row-level scoping).”

“Backend engineer who built and evolved the real-time networking/messaging backend for a cross-platform professional networking app (Make Connexions), optimizing for low-latency delivery, privacy, and strong consistency. Experienced scaling Python/FastAPI APIs with async + Redis, and leading safe refactors via versioned endpoints, feature flags, and backward-compatible migrations; strong production auth/RLS expertise including refresh-token rotation edge cases.”

“Backend/data engineer who reports building production Python services (FastAPI + JWT) backed by Postgres and Redis, and modernizing data workflows using AWS Glue + PySpark with S3/RDS. States experience delivering AWS solutions (S3, SES, Cognito) and using golden datasets/snapshot testing for migration parity, with many details withheld due to NDAs. Seeking fully remote work with a $300k base salary expectation.”

“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”

“Backend-focused Python engineer who has owned production FastAPI services deployed on Kubernetes, including CI/CD (GitLab CI to ECR) and GitOps delivery via ArgoCD/Helm. Has hands-on experience with complex reliability and infrastructure work—solving data inconsistency with validation/partial-data paths, fixing K8s liveness issues via lazy loading, and supporting a phased cloud-to-on-prem migration with dual-writes and monitoring. Also built Kafka-based real-time ingestion consumers handling bursty, high-throughput traffic with async processing and topic/retention tuning.”

“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”

“Backend engineer with experience in both healthcare (Siemens) and payments (Bitwise), focused on scaling Python APIs and modernizing architectures. Has led monolith-to-microservices migrations and introduced Kafka async processing, Redis caching, and ELK observability, citing ~40% faster issue resolution and improved reliability via idempotency and strong security controls (OAuth2/JWT, RBAC, RLS).”

“Built and deployed a production LLM-powered support assistant for customer support agents using a RAG architecture over internal docs and past tickets, with human-in-the-loop review. Demonstrates strong applied LLM engineering focused on real-world constraints (hallucinations, latency, cost) using routing to smaller models, reranking, caching, and rigorous evaluation/monitoring (offline eval sets, A/B tests, KPI tracking).”

“At FiVerity, built and deployed a production LLM/RAG-based Information Gathering Tool for credit union fraud analysts that generates auditable investigation summaries from verified evidence. Focused on high-stakes constraints—hallucination prevention, cross-entity leakage controls, compliance/PII-safe monitoring, and latency—while also shipping customer-facing agentic workflows using CrewAI and LangGraph in close partnership with fraud and compliance stakeholders.”

“Full-stack developer with 4 years of experience and an MS in Computer Science who led frontend delivery for a large airline platform (booking, check-in, and payment flows) using Angular/TypeScript with a Java backend. Emphasizes quality at scale via SonarQube monitoring, E2E/regression testing, and iterative Agile collaboration with clients using Figma.”

“Software engineer (Yellow.ai) who built and productionized an AI-driven resume tailoring system using embeddings + Chroma RAG + QLoRA fine-tuning, deployed via Docker/Kubernetes with CI/CD on a CPU-only Oracle VM. Demonstrates strong reliability/evaluation rigor (custom hallucination/coverage/relevance metrics) and measurable business impact, including a 60% user satisfaction lift from improving chatbot intent accuracy with product and support teams.”

“Frontend engineer who has owned end-to-end delivery of multi-step commerce workflows, including an e-commerce cabinet customization platform and a food/grocery pickup ordering flow. Emphasizes scalable React architecture (Redux/RTK Query), strong automated quality (TDD, Jest/RTL, ESLint/Prettier/Husky), and performance/cost optimization via API caching and reduced AWS Lambda calls.”

“Cloud/ML engineer with production deployment experience on Azure (Dockerized models, managed APIs, data pipelines) who has repeatedly stabilized unreliable systems—e.g., taking an API-driven analytics pipeline from ~60% to 98% reliability and an Azure ML service from ~80% to 97% by addressing rate limits, container memory, and gateway timeouts. Also built an explainable contract-risk model for entertainment bookings (Transformers + SHAP) and integrated it into a legacy booking system via a Flask REST API, plus prior IoT work at Nissan processing CAN bus sensor streams for diagnostics/anomaly insights.”

“Built and deployed a production enterprise LLM-powered RAG assistant for the construction domain, enabling natural-language querying across PDFs/reports and structured sources (SQL/CSV). Implemented an agent-based routing and multi-agent orchestration approach (LangChain/LangGraph) to reduce hallucinations, improve latency, and deliver actionable, structured responses based on stakeholder feedback.”

“Internship project at Builder Market: built an end-to-end production multimodal LLM application that estimates renovation/replacement costs from appliance photos (CLIP embeddings) or text descriptions, combining fine-tuning with agentic RAG. Focused heavily on real-world performance constraints—latency and cost—using parallel agent workflows, model routing to smaller/open-source models, re-ranking, and retrieval chunking, and collaborated closely with CEO/co-founders to deliver the solution.”

“AI/ML Engineer at Fifth Third Bank who has shipped production fraud detection and risk analysis systems combining ML models with LLM-powered insights/explanations, including real-time monitoring, drift detection, and automated retraining under regulatory explainability constraints. Also built a hybrid-retrieval internal knowledge-base QA system (+20% top-5 relevance) and delivered a customer support chatbot that reduced first response time by 30% through strong stakeholder collaboration.”

“Built and deployed a real-time hospital readmission risk prediction system at NYU Langone Health, combining structured EHR data with BERT-based NLP on clinical notes and serving predictions to clinicians via Azure ML and FHIR APIs. Emphasizes production reliability and clinical trust through SHAP-based explainability and robust healthcare data preprocessing, and reports a 22% reduction in 30-day readmissions.”

“Full-stack developer with Manulife experience building and scaling a customer-facing digital wealth portfolio tracker and a complex React/TypeScript portfolio dashboard. Strong track record improving mobile UX and reliability with measurable impact (30% lower mobile bounce rate; ~20–22% fewer Stripe payment errors) through CI/CD automation, A/B testing, and monitored incremental rollouts.”

“Frontend engineer (Cyderes) specializing in security analytics/SOC dashboards, building complex multi-tenant React + TypeScript interfaces for near real-time authentication and MFA monitoring. Known for scaling quality via strict TS, shared contracts, CI-enforced multi-level testing, and performance optimization, plus pragmatic incremental refactors and gated rollouts that protect active customer workflows.”