Vetted API Integration Professionals

“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.”

“Healthcare-focused software engineer/lead who has delivered customer-facing portals and internal call-center tools, including rebuilding a legacy Adobe Flash call center app into a modern TypeScript frontend with NgRx state management. Experienced leading onshore/offshore teams, integrating healthcare APIs, and driving adoption by visiting call centers to capture user workflows and bake them into regression testing—work that proved especially valuable during COVID-era shifts to video appointments.”

“AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.”

“Growth creative/performance marketer from BYJU'S (India) who runs disciplined creative experimentation across Meta, TikTok, and YouTube. Notably shifted messaging from feature-led to outcome/testimonial-led creative, delivering CPA down 27%, ROAS up 35%, and +11% trial-to-paid conversion, and has experience leading a small creative pod (editors + writer) with a rapid-iteration production system.”

“Solo developer who shipped an Android game (Master Caster) built around touch gesture recognition (P$ algorithm) and data-driven potion/ingredient systems using JSON/dictionaries. Has hands-on experience optimizing Unity projects for mobile constraints (framerate, heat/battery) using techniques directly applicable to VR, and is actively porting the game to VR in Unreal with a focus on accessibility and room/standing/seated play modes.”

“AI/ML infrastructure-focused engineer who has built production RAG systems from scratch (Supabase/pgvector + OpenAI embeddings) and iterated using formal eval metrics to improve retrieval quality. Also debugged real-time audio issues in a LiveKit-based pipeline by correlating packet loss with VAD behavior, and has deep experience building brittle, customer-specific financial platform integrations in Python/Playwright (2FA, redirects, token refresh, rate limits).”

“Software engineer with experience at Dollar Shave Club and Mudflap, focused on user-driven product delivery and cross-team alignment. Built an Okta SSO-based internal portal (React/Node) centralizing access to org services, and has hands-on experience diagnosing LLM/agent workflow issues via instrumentation and systematic triage. Known for translating between product/customer needs and engineering tradeoffs to ship quickly while planning stabilization and scalability.”

“LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.”

“Software engineer with startup and capstone experience who improved an ~8-hour database refresh workflow by moving API calls to asynchronous execution and then addressing API rate limits via throttling. Emphasizes performance profiling/logging, strong developer onboarding documentation practices, and disciplined Agile/Jira bug triage and expectation-setting with stakeholders.”

“LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).”

“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.”

“Co-founded a healthcare AI startup building and deploying software directly with end users, emphasizing rapid shipping, deep user interviews, and workflow-first adoption. Has hands-on production deployment experience on AWS (including diagnosing a silent AWS App Runner failure caused by an ARM vs amd64 Docker build mismatch) and is motivated by customer-facing, travel-heavy roles to keep engineering tightly connected to real-world usage.”

“Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.”