Vetted Workflow Automation Professionals

Pamela Shand

Screened

Director of Talent Acquisition specializing in workforce planning, analytics, and internal mobility

Newark, NJ19y exp

“Operations and talent strategy leader who has supported two early-stage tech startups by optimizing org structure and building scalable recruiting operations. Implements KPI-driven hiring systems, employer branding/attraction strategies, and DEI/SMART/SWOT frameworks, and has a concrete example of reducing declined offers by shifting compensation discussions earlier and training hiring managers. Experienced mentoring founders/executives through mission-aligned, flexible development plans and structured communication processes.”

“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”

Andrew Liang

Screened

Intern Software Engineer specializing in full-stack and AI/ML systems

2y exp

“Software engineer with experience at Amazon and Agora building end-to-end systems: a knowledge-base AI chatbot (React/TypeScript UI + retrieval/response backend + Docker deployment) and an internal approval governance platform using AWS Step Functions and DynamoDB. Emphasizes fast iteration without sacrificing trust via feature-flag rollouts, citation-required answers, abstention on low-confidence retrieval, regression query sets, and strong observability (request IDs, structured logs, latency/error monitoring).”

Jacqueline Zhang

Screened

Mid-level Machine Learning Engineer specializing in LLMs, fairness, and healthcare ML

Illinois, USA4y exp

“ML/NLP practitioner with a master’s thesis focused on domain-adaptive knowledge distillation for LLMs (LLaMA2/sheared LLaMA), showing improved perplexity and ROUGE-L on biomedical data. Also built real-world data linking and search systems: integrated ClinicalTrials.gov with FAERS using fuzzy matching + embeddings, and delivered an LLM-powered FAQ recommender at Hyperledger using sentence-transformers, FAISS, and fine-tuning to mitigate embedding drift.”

“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”

Asrith Velireddy

Screened

Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems

Harrison, NJ4y exp

“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”

Adam Wermus

Screened

Senior Data Engineer & Render Tools Developer specializing in VFX and render farm pipelines

Santa Monica, CA7y exp

“Real-time simulation/physics engineer who optimized character effects and cloth for the "Infinity" game by implementing and profiling multiple ODE integrators, including pioneering the largely undocumented Parker-Sochacki method (optimized 5/7 sims; >30% speedup on a particle system). Also built SPH fluid solvers in Unity (C#) and created Grafana/Python Dash dashboards to analyze latency/throughput, with strong interest in applying math/physics and tooling to soccer/football gameplay.”

“Operations leader with Amazon experience owning a founder-level initiative during national supply chain Regionalization, building and scaling a "Stack-to-Light" operating mechanism to standardize non-sortable FC execution with instrumentation and balanced-scorecard metrics. Later joined Revivn to stabilize an underperforming operation by developing frontline leaders and aligning ops with finance and GTM through clear KPIs and operating cadence.”

“UI/UX and product-minded designer with experience shaping digital products from concept to launch across telecom and higher education. Notably pitched a new Globe Telecom app that became the basis for the product after joining, helped launch it within five months, and contributed to a 4x subscription lift through A/B-tested in-flow upsell design.”

“AI/LLM-focused engineer with hands-on experience building RAG pipelines, prompt engineering workflows, and multi-agent systems using tools like LangChain. Stands out for combining AI-assisted development with production-grade validation and for leading the architecture/orchestration of agent-based recommendation systems that improved response time, accuracy, and scalability.”

Donnell Mata

Screened

Director-level Strategy & Operations leader specializing in GTM, product, and operating cadence systems

San Francisco, CA22y exp

“Operator/strategy leader with experience driving digital transformation and building executive operating systems in high-noise environments. At a legacy B2C brand, created a prioritization framework and exec alignment process that cut 100+ initiatives to 16 and lifted execution from 12% to 81%. At Point B, owned a $20M delivery budget while shifting the firm to a tech-forward practice, implementing OKR/KPI cadences and AI-enabled workflows (n8n, LLMs, gamma.ai) that materially improved executive productivity.”

“Built both traditional data infrastructure and LLM-powered product workflows, spanning a Python/SQL ETL deployment at Amazon and an adaptive learning system for their DataLingo platform. Particularly interesting for roles at the intersection of data engineering, applied AI, and customer-facing product delivery, with hands-on experience stabilizing probabilistic LLM systems in production.”

Josh Rhoades

Screened

Executive Technology Leader (CTO) specializing in AI-enabled SaaS and regulated platforms

Los Angeles, CA30y exp

“Senior engineering leader with experience at Disney and BlackLine who drives business-aligned technology roadmaps through deep Product/Engineering partnership (two-in-a-box) and pragmatic prioritization frameworks. Has led major modernization initiatives—private-to-public cloud migration to GCP with multi-cloud evolution, data-layer performance improvements (Mongo/Redis, caching/query optimization), and tooling upgrades (VSS to GitHub)—while scaling teams with strong quality and accountability culture.”

“Player Experience developer on Madden who shipped player-facing Weekly Recap and Halftime Show flows built in visual scripting, including a custom solution to keep full-screen UI persistent across level loads with strong logging and failsafes. Also builds networked UE co-op ARPG systems (talent trees, combat/animation, leveling/stats, AI, dynamic spawning) and has a track record of refactoring shared UI/banner logic into scalable prefabs to reduce bugs and improve team workflow.”