Vetted Sprint Planning Professionals

“Operations- and growth-oriented candidate who improves external partner workflows through standardization and measurement (cut turnaround time ~40% while maintaining 99% accuracy). Also launched and scaled a university Excel/data analysis workshop using ICP-driven GTM and a tracked acquisition loop, increasing attendance 15% and generating 95% repeat-demand intent.”

“LLM workflow builder who has deployed a personalized GPT experience (including Delphi AI-based knowledge ingestion) and built a LangChain/LangGraph job-aggregation pipeline that ingests, normalizes/dedupes, filters, then uses an LLM to rank and summarize matches. Emphasizes production reliability with structured outputs, retries/fallbacks, metric-driven evaluation, logging/prompt versioning, and A/B testing, and collaborates with non-technical stakeholders through demo-driven iteration.”

“Game QA professional with AAA open-world shipping experience, owning high-impact quality risks like save-data corruption, progression blockers, performance drops, and multiplayer desync. Demonstrates strong systems thinking and exploit prevention (e.g., reproduced and helped fix a reward-duplication race condition using network interruption + rapid input), with disciplined JIRA/TestRail workflows and evidence-driven bug reporting.”

“Business/partnerships-focused project/program leader with government contracting (SLED) experience who supported a cybersecurity solicitation response for Amtrak after a breach, using NIST-aligned posture assessment and recommending MFA, Zero Trust, and incident/vulnerability registers. Also led an urgent COVID-era recovery from a server crash by coordinating a move to AWS EC2 and managing vendor negotiation and project timelines for a CRM platform serving the winery/beverage industry.”

“Software engineering intern with hands-on ownership of a Java/Spring Boot order management microservice, including production performance tuning via Redis caching and database indexing driven by API logs/metrics. Also contributed to a production mobile-backend LLM feature using RAG with embeddings over structured data and documents (DB + object storage), with guardrails to keep responses grounded.”

“Full-stack engineer with deep startup experience building products from scratch under ambiguous requirements. Delivered a scalable, admin-configurable notification platform (Spring Boot/Java/Kafka) supporting 50+ notification types across 3 channels for 10k+ users, cutting new notification setup to ~5 minutes. Also built a Tinder-meets-LinkedIn job-swiping app (React/TS + Node/Prisma) and has hands-on AWS production ops (ECS/EKS, RDS, CloudWatch) plus multiple third-party integrations (Stripe, QuickBooks, Twilio).”

“Frontend engineer at LodestonePM who led end-to-end delivery of an AI release-notes generator (OpenAI API) and a Kanban-style release board in Remix/React/TypeScript. Demonstrated scalable architecture (bridging tables, upserts), strong QA practices, and measurable performance wins (200+ item loads reduced from 10–20s to a few seconds via caching/pagination), plus UX improvements like simplifying a Jira integration flow.”

“Full-stack engineer with strong production experience improving performance and reliability of data-heavy analytics products. Has shipped end-to-end features spanning Node/Express + PostgreSQL + Redis and React/TypeScript, deployed via Docker/GitHub Actions to AWS EKS with Helm, and monitored with Datadog/CloudWatch; also built a Python compliance automation backend for AWS security monitoring with RBAC, versioned REST APIs, and resilient throttling-aware processing.”

“Frontend engineer/team lead currently overseeing a 5-person team building an AI trading mobile application, using modular architecture and Jest-based testing to maintain quality as features scale. Also develops a trading/research platform in Next.js/React/TypeScript with Tailwind and Redux, including complex broker registration workflows and experience separating on-device AI components from core business logic.”

“Full-stack engineer with strong AWS operations experience who helped replace a long-standing manual logistics reporting process by building a production-grade, event-driven On-Time-Performance rules system. Personally owned the Vue-based rule configuration frontend end-to-end (design collaboration through QA/UAT and post-release support) and measures success via accuracy validation against historical data, reduced manual adjustments/tickets, and system latency/error metrics.”

“Frontend engineer who has led end-to-end delivery of internal and analytics dashboards in React + TypeScript, with a strong emphasis on scalable architecture, disciplined state separation, and performance under real-time data loads. Uses practical profiling (React Profiler/DevTools), virtualization, and feature-flagged rollouts with solid QA and rapid post-launch iteration to keep quality high as products scale.”