Vetted Requirements Gathering Professionals

Timothy Washington

Screened ReferencesStrong rec.

Senior Product Manager specializing in AI-powered products and responsible AI

Cranbury, NJ18y exp

“Mission-driven product and program leader who built WhatsApp’s talent inclusion infrastructure from scratch and later applied AI at Google to scale inclusive product evaluation across 25+ teams, including Gemini. Brings a rare mix of product systems thinking, human-centered AI judgment, and lived experience growing up in public housing that deeply informs their focus on equity, access, and accountable technology.”

“Engineer with startup experience building AI-powered internal knowledge and support products from ambiguous early-stage concepts into production systems used by multiple teams. Particularly strong in end-to-end LLM product delivery across backend orchestration, retrieval, observability, security, and full-stack user experience, with clear impact on productivity and self-service adoption.”

Tolulope Akinlabi

Screened ReferencesStrong rec.

Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk

Lanham, MD6y exp

“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”

Padmaja Tyada

Screened ReferencesStrong rec.

Executive engineering leader specializing in cloud, AI, and FinTech platforms

San Jose, CA25y exp

“Engineering leader with experience scaling teams from 25 to 60+ and delivering both enterprise platform modernization and AI-native product innovation. At Experian, he led an AWS transformation of a high-volume credit platform serving 250M+ consumers, achieving 10x performance gains and 30% cost reduction; at Channel Core, he built AI-powered creator tools using OpenAI and RAG that improved adoption and personalized outreach outcomes.”

“Recruiting leader with experience at Google and YieldStreet who combines people management with a heavy personal requisition load (15–20). Partnered directly with HRBPs and the CFO on international/executive hiring, budgeting, equity decisions, and board-level quarterly planning. Led a department-wide ATS replacement and enforced interview training/compliance and SLAs to improve data quality and time-to-fill.”

Alex Kittredge

Screened ReferencesStrong rec.

Executive People Strategy & Transformation Leader specializing in workforce planning and operating models

Brooklyn, NY8y exp

“Senior Program Manager / HR Chief of Staff (Global Industrial) specializing in cross-functional risk remediation, HR systems implementations, and M&A compliance. Delivered measurable outcomes including closing 18 payroll audit findings in 16 weeks, rolling out SAP SuccessFactors performance management to 2,000+ employees with major adoption gains, and remediating 600 I-9s in 6 weeks to avoid ~$3M in exposure; experienced operating with high confidentiality across large-scale M&A.”

Denis Siminiuc

Screened

Junior Research Assistant specializing in LLMs, NLP, and data systems

Cambridge, MA3y exp

“Software-focused candidate who built a data monitoring pipeline during a hedge fund internship, integrating real databases and an email API to notify teams when data was ready. Comfortable working through legacy/scrappy code and uses LLMs to accelerate comprehension and delivery, with an emphasis on thorough testing and clear communication with stakeholders/customers.”

“Financial engineering analyst at BlackRock who has built internal data products for thousands of sales users, including an end-to-end fund comparison system that combines internal and third-party data into compliance-approved PDFs. Brings a mix of data engineering, stakeholder-heavy delivery, and emerging AI experimentation, with current work focused on regression testing and Snowflake-based portfolio data automation.”

“Entrepreneurial healthcare operator currently serving as investor, co-founder, and COO of Mednevo, a startup combining AI with physician oversight rather than replacing doctors. Brings experience from 8 startups, prior capital raising, and a practical approach to healthcare AI trust, including doctor-controlled AI shutoff, HIPAA-minded compliance, and physician validation of LLM outputs.”

“Senior product engineering and data architecture leader who has owned end-to-end solutions for enterprise analytics and legal search platforms, including work for Sony Pictures Entertainment and Accenture Legal. Combines executive-level architecture and team leadership with hands-on experimentation in modern AI systems, recently building a multimodal Hugging Face agent that significantly exceeded its benchmark score.”

“Enterprise cloud/SaaS customer success leader who owned a strategic $102M Azure commitment end-to-end, rescuing a Kubernetes migration by formalizing Sev A/B triage/escalation ownership and executive governance. Drove measurable outcomes including restored executive confidence and consumption growth from $1M to $2M/month (~30% adoption growth) by tying stabilization milestones to migration velocity, forecasting, and expansion strategy.”

“Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.”

“P&G operator who is also building and selling an AI receptionist (voice agent) SaaS for healthcare/service clinics, using EHR + calendar API compatibility to target accounts and letting the Voice AI run parts of the demo to prove value. Has already closed and deployed to two clients in the last two months, with production impact via reduced front-desk overhead and automated scheduling/FAQs, and brings a structured, scalable deployment/process mindset from global WMS rollouts.”