Vetted AWS Professionals

“ML/NLP engineer with experience at Flatiron Health building a production NLP platform that processed millions of clinical notes, using BERT/BiLSTM-CRF and spaCy to extract and normalize entities from noisy EMR text with oncologist-in-the-loop validation. Also built scalable retail ML workflows (Spark + Kubernetes + feature store caching) and applied vector databases plus contrastive-learning fine-tuning to improve retrieval relevance and recommendations.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”

“Senior engineering leader from Goodyear’s AndGo startup-like division who scaled the org from 12 to 30+ across pod-based teams and introduced an Architect Guild/ARD governance model. Led a 4-month Europe launch requiring AWS regional infrastructure, GDPR compliance, i18n/l10n, and new EMEA reporting pipelines, and has hands-on depth in API performance, incident response, and GraphQL/Hasura adoption to boost product velocity.”

“Open-source maintainer of KafkaJSUI, a Vue.js-based Kafka browser UI, focused on making large-topic exploration fast and responsive. Delivered major performance wins (incremental fetching, virtualized lists, WebSocket streaming, backpressure, Web Worker offloading) cutting load times to sub-200ms, and also strengthened CI and developer documentation while handling community-reported issues end-to-end.”

“Backend/automation engineer who led the design of an OOP Python test automation framework for AWS infrastructure (Behave + Jenkins), cutting regression effort from weeks to a 3–4 hour run. Has hands-on cloud and DevOps experience across AWS (boto3, ECS, AMI automation via GitHub Actions) plus data/migration work including on-prem-to-cloud Oracle Retail DB migration with rollback planning and a Kafka + ML fraud-detection streaming pipeline.”

“Hands-on technical professional experienced in taking LLM/AI-adjacent integrations from prototype to production, using customer observation to refine UX and uncover edge cases. Diagnoses workflow issues in real time using logs and Sankey-style workflow analysis, and communicates fixes with clear short/long-term plans plus proactive alerting. Also partners cross-functionally to drive adoption and cost savings, including a POC around IBM Sterling Integrator that reduced licensing costs by $30K/year.”

“QA tester with hands-on experience across web, mobile, and API testing, including requirements gathering, test planning/case creation, and executing system/regression/UAT. While new to console game testing and platform certification checklists (TRC/XR/LOT), they emphasize strong testing fundamentals, API automation experience, and using AI tools to ramp up quickly.”

“ML Engineer with recent Goldman Sachs experience building and deploying a production RAG/LLM assistant for summarization, drafting, and internal knowledge retrieval across financial, risk, and compliance documents. Designed for heavy regulatory constraints and scaled to 10,000+ concurrent users using Kubernetes-based orchestration, dynamic LLM routing, and rigorous testing (adversarial prompts, A/B tests, load simulations) with privacy controls like differential privacy.”

“Software engineer who built and deployed OddPulse, a multi-agent LLM-powered continuous financial auditing system aimed at reducing compliance penalties by catching issues before audit cycles. Experienced with TrueAI-based agent orchestration, Airflow on GCP batch workflows, and rigorous evaluation/benchmarking (hit rate/MRR, latency/TTFT, cost) alongside security controls for sensitive financial data.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Engineering manager leading a 15-person team at FBN on the Gridbull platform, shipping a self-serve pricing/quoting tool for structured commodity products using real-time futures market data. Owns architecture and reliability for third-party data integrations (WebSocket + REST fallback), including resolving a day-one production incident caused by undocumented vendor connection resets. Introduced lightweight Technical Implementation Plans to improve cross-functional alignment and delivery speed in a high-growth environment.”

“Former CTO/CTPO with hands-on experience supporting co-founders through pre-seed to Series B fundraising, including investor technical due diligence and architecture deep-dives. In a logistics company, led a customer-interview-driven effort applying AI and workflow tools that cut customer busywork by ~30% in the first iteration, and has experience planning delivery with onshore/offshore teams (LATAM/India).”

“CTO who ties technology strategy directly to business outcomes, building multi-year roadmaps with measurable ROI. Led major modernization (cloud, data platform, unified API, microservices + CI/CD) delivering 5x faster releases/deployments, 99.8% uptime, and 40% user growth without headcount increases, while scaling engineering from 15 to 80+ in ~18 months.”

“Full-stack engineer with startup experience who owned end-to-end features on Impact’s Hiring Solutions platform, including a hiring inbox spanning React UI and Postgres data models; the product helped drive 500+ jobs filled shortly after launch. Comfortable designing modern React/TypeScript + Node architectures (GraphQL, testing, migrations) and operating on AWS (RDS, EC2/Fargate, S3, Datadog, CircleCI). Also founded their own startup (Bibbr) and made early-stage stack/infrastructure decisions under high ambiguity.”

“Healthcare diagnostics/health tech founder building Casandra.ai, an API-driven lab test catalog and ordering platform designed to standardize fragmented test catalogs and integrate into provider workflows via FHIR. Bootstrapped and built a deploy-ready product, drawing on prior startup experience and accelerator participation (Health Box, DreamIt Ventures).”

“IT leader with hands-on M&A integration experience (including day-one readiness) across notable brands (e.g., Billabong, Marucci Sports) and product-focused organizations (Oakley). Brings broad IT domain expertise (AI, business systems, digital sales technologies) and has worked with multiple startups; interested in joining an existing startup to help it scale rather than founding a new company.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with strong real-time and applied AI experience: built an internal AI “virtual subject matter expert” platform at Shell Energy serving ~1,800 employees with sub-200ms response streaming. Diagnosed AWS load balancer WebSocket disconnects and shipped reliability fixes (heartbeats, reconnect/backoff, session resume), and implemented AI production guardrails (eval suite, drift monitoring, confidence thresholds, citations, human-in-the-loop) that reportedly cut hallucinations by ~90%.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

“Full-stack TypeScript engineer who built and operated a production order/inventory platform (React + NestJS/Node + PostgreSQL) with Redis and RabbitMQ for performance and background workflows. Emphasizes correctness in production via idempotency, retries/backoff, DLQs, and observability, and has also delivered external-facing REST APIs (Swagger, versioning, JWT/RBAC) plus resilient checkout browser automations using Playwright/Puppeteer.”

“CTO candidate with experience supporting startups targeting Series A/Series B funding and a strong grasp of how funding choices affect ownership. Emphasizes building clean-slate architecture and organizations, and uses market/UX research plus AI-enabled rapid prototyping and architectural trade-off analysis to validate ideas quickly.”

“Built and operated a production TypeScript backend for a stateful conversational quoting chatbot at Tringapps, orchestrating multi-step workflows and session state while integrating with Salesforce and NetSuite. Implemented validation/retry logic, modular architecture, and strong logging/observability to handle real-world edge cases and external API failures.”

“DevOps engineer focused on CI/CD who built and productionized LLM/MCP-based chat agents integrated into Cisco Webex to help developers troubleshoot PRs and pipelines via GitHub/Jenkins data. Strong in operationalizing agentic systems with observability (OpenTelemetry/Grafana), user-scoped rate limiting, and Kubernetes-based scaling, and has presented demos on agent SDK capabilities and DORA metrics dashboards.”

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”