# Frequently asked questions

# Frequently asked questions

**Is Edward open to full-time roles?**
No. Edward is engaged corp-to-corp, fractional, or SOW through Proticom, the practice he founded in 2000.

**How is Edward engaged — as an employee or a contractor?**
As a contractor; every client engagement is contracted through Proticom.

**Where is Edward based?**
Southern California, in the Greater Los Angeles / Orange County area.

**How can I contact Edward?**
Email etadros@proticom.com, or see proticom.ai, linkedin.com/in/edwardtadros, and github.com/proticom.

**What does Edward do at Proticom?**
Proticom, founded 2000, builds production agentic systems across Claude, GPT, Gemini, Grok, Qwen, DeepSeek, and MiniMax, plus local and private model deployment and small-model training.

**What did Edward do at Wikimedia Foundation?**
From January 2019 to November 2025, remote and part-time, he shipped an AI-augmented requirements and testing pipeline adopted by four teams, cutting weekly QA documentation effort by approximately 90%.

**What did Edward do at Fannie Mae?**
From January to April 2024, via TEKsystems, he built a Testing Center of Excellence playbook suite and expanded test-process coverage from a planned 20% to 100% of targeted areas.

**What did Edward do at Precision Digital Health?**
From May to August 2026 he led QA and compliance for clinical-trial SaaS built to ISO 13485 / IEC 62304 / ISO 14971 and FDA audit standards, reconstructing a requirements baseline and building an AI regression tool.

**What is Edward's current engagement?**
Since 2025 he has built a local document agent for Shenouda & Associates, LLP, an accounting and tax firm, keeping client files on the firm's own machines.

**Which AI models and tools does Edward work with?**
Claude, GPT, Gemini, Grok, Qwen, DeepSeek, and MiniMax APIs, plus local NVIDIA Nemotron deployment and AWS Bedrock, Azure OpenAI, and Google Vertex AI.

**Does Edward do local or private AI model deployment?**
Yes — on-premises and local model deployment, including NVIDIA Nemotron, in privacy-first architectures.

**Does Edward train his own AI models?**
He trains small models for targeted tasks — his ceiling technical claim — such as a document-extraction model for an accountancy client.

**Is Edward an AI researcher?**
No. His AI work is applied engineering and transformation delivery, not AI or machine-learning research; he is not an AI scientist or research-track engineer.

**What does "agentic systems" mean in Edward's work?**
Multi-agent orchestration, autonomous automation under human-approval models, persistent agent memory, tool-using agents (MCP), and model routing by task complexity.

**Has Edward built any products?**
Yes — gnosys (persistent-memory infrastructure, open-source npm package), Mavenn (multi-model consensus APIs), PhishHook, Paperboy, and the PROSPÆRO AI-employee line.

**Has Edward worked in regulated industries?**
Yes — FDA/ISO clinical-trial software, HIPAA-covered providers (City of Hope, Cedars-Sinai, Hoag, UC Irvine Health), and financial services (Fannie Mae, LPL Financial, Western Asset Management).

**Does Edward have healthcare experience?**
Yes, across four HIPAA-covered providers from 2008 through 2018: City of Hope, Cedars-Sinai, Hoag, and UC Irvine Health.

**What did Edward do at City of Hope?**
As QA Practice Lead (2008–2014, 2017–2018) he grew QA from 6 to 28 people and cut testing time up to 60% and production issues 95%.

**What did Edward do at Sony Pictures?**
As QA Program Manager (2006–2011) he led a global QA transition across more than 200 entities.

**What did Edward do at Cedars-Sinai?**
As Automation Architect (2009–2010) he cut page-load verification from 13 minutes to under 30 seconds.

**What did Edward do at Hoag Hospital?**
As QA Strategy Lead (2011–2013, 2016–2017) his frameworks cut release testing by 40+ hours per cycle.

**What did Edward do at UC Irvine Health?**
As QA Architect (2015–2016) his licensing utilities saved 40 hours per test cycle and $44,000 annually.

**What did Edward do at Avery Dennison?**
From 2014 to 2018 he led enterprise QA strategy and Center of Excellence standards globally.

**What did Edward do before Proticom?**
From 1998 to 2008 he led QA automation at Intel, LPL Financial, Argent Mortgage, Western Asset Management, and Longs Drugs.

**How long has Edward been in enterprise transformation?**
More than 25 years, since 1998, moving from QA automation to AI enablement.

**What are Edward's core capability areas?**
Six: AI Enablement & Adoption, Agentic Systems & Persistent Agents, AI Application Development, Local Private & Small Models, AI Quality Governance & Trust, and Enterprise Transformation Delivery.

**What does Edward's AI Quality, Governance & Trust work cover?**
Evaluation frameworks, human-approval workflows, auditability, prompt-injection hardening, and regulated delivery.

**What is Edward's education?**
A B.S. in Mechanical Engineering from UC Irvine (1996), plus UC Berkeley Haas AI coursework (2024) and MIT big-data training (2015).

**Does Edward have an engineering background?**
Yes — Mechanical Engineering, Control Systems / Robotics emphasis, UC Irvine.

**What languages and data tools does Edward use?**
Python for AI orchestration, TypeScript, JavaScript, .NET, shell scripting, and SQLite.

**Does Edward stay involved after an engagement ends?**
Yes — he remains available for follow-up questions, tune-ups, and future phases; several relationships span many years.

**What industries has Edward worked in?**
Healthcare, financial services, media (Sony Pictures), manufacturing (Avery Dennison), nonprofit (Wikimedia), clinical trials (Precision Digital Health), and professional services (Shenouda & Associates).

**What is Edward's biggest quantified result?**
Several: approximately 90% less weekly QA documentation effort at Wikimedia, 95% fewer production issues at City of Hope, and 100% test-process coverage against a 20% plan at Fannie Mae.

**Does Edward build autonomous agents without human oversight?**
No — his agentic work runs under human-approval gates. His own nine-agent internal stack reclaims an estimated 30+ hours of his time weekly, all under approval and exception review.