Chief Technology Officer / Founding Technical Lead

Chief Technology Officer / Founding Technical Lead
ShortSight AI

Location: Remote / Hybrid flexible
Type: Full-time or fractional-to-full-time
Compensation: Cash + meaningful equity, based on stage and commitment
Reports to: CEO / Founder
Company: ShortSight AI

About ShortSight AI

ShortSight AI is building an AI-powered forensic research platform for hedge funds, short-biased investors, forensic analysts, whistleblowers, and investigative teams.

The platform ingests SEC filings, earnings transcripts, insider activity, capital markets data, adverse media, and alternative data to surface red flags before the market catches up.

ShortSight helps users identify accounting games, governance failures, dilution risk, leverage cliffs, suspicious executive behavior, fake growth narratives, footnote changes, auditor issues, insider selling, and other early warning signals that traditional research workflows often miss.

We are not building another dashboard.

We are building a forensic intelligence engine that can:

Pull filings
Compare footnotes
Detect language changes
Map risk signals
Score red flags
Generate citation-backed reports
Show analysts where to look next
Turn scattered market noise into an actionable short thesis
The Role

We are looking for a CTO / Founding Technical Lead to take ownership of the ShortSight AI technical stack, product architecture, data pipelines, AI workflows, and engineering roadmap.

This person will replace and expand the role currently held by our CTO, who has become unavailable due to health issues.

This is a hands-on leadership role. Early stage means no hiding behind strategy decks. You should be able to architect, build, debug, ship, and manage contractors or junior engineers when needed.

The right person will understand that our moat is not just “AI.”
Our moat is forensic logic + data architecture + source traceability + workflow speed.

What You’ll Own

1. Platform Architecture

You will own the technical architecture for an AI-native forensic research platform.

Current / expected architecture includes:

LLM-driven research workflows
RAG over SEC filings, transcripts, news, and market data
Structured forensic signal extraction
Source-cited outputs
Report generation
Dashboard modules
Alerts
User/workspace management
Data ingestion pipelines
Scalable backend infrastructure

The product needs to be fast, credible, defensible, and usable by financial professionals.

1. Data Ingestion & Processing

You will help build or improve pipelines for:

SEC EDGAR filings
10-K, 10-Q, 8-K, S-1, S-3, DEF 14A
XBRL data
Earnings transcripts
Insider Form 4 activity
Institutional ownership flows
Short interest and borrow data
Options volatility / skew indicators
Press releases
Adverse media
Social sentiment where useful
Peer comps and sector data

The key is not just pulling data.
It is making the data usable for forensic analysis.

1. AI / LLM Workflows

You will own the AI research engine.

Prompt architecture
Retrieval pipelines
Model orchestration
Citation-backed generation
Structured outputs
Risk scoring
Agentic research flows
Human-in-the-loop review
Error checking
Hallucination controls
Output QA

This is especially important because our users cannot afford sloppy AI nonsense. Hedge funds and analysts need to trust the chain of evidence.

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The platform should never say, “trust me bro.”
It should say, “here is the claim, here is the source, here is the risk, here is why it matters.”

1. Forensic Signal Engine

You will help translate our research methodology into software.

Revenue quality
Accounting risk
Margin inconsistencies
DSO / AR movement
Dilution risk
Going concern language
Debt maturities
Covenant pressure
Auditor changes
Insider selling
Related-party transactions
Customer concentration
Promotional management language
Legal / regulatory issues
M&A accounting games
Governance failures
Squeeze risk
“Why the market should care” analysis

This is where ShortSight becomes more than a chatbot.
We need someone who can turn messy human research logic into repeatable software workflows.

1. Productization

You will help move ShortSight from custom research / intelligence-as-a-service into a repeatable SaaS product.

Company screener
Fraud Fingerprint Index
Short thesis generator
Red flag dashboard
Evidence pack builder
Auto-generated PDF / Word reports
Analyst review workflow
Alerts by ticker / signal / severity
Team workspaces
Audit logs
Slack / email notifications
API access for enterprise users

The goal is not to build every feature at once.
The goal is to know what to build first, what to fake manually, what to automate, and what to kill.

First 90 Days
First 30 Days — Stabilize and Understand
Audit current codebase, architecture, data flows, and AI workflows
Identify what is real, what is brittle, and what is duct tape
Document the current platform
Review existing customer/report workflow
Map technical debt
Identify security, data, and reliability risks
Create a realistic engineering roadmap
Days 31–60 — Ship the Core
Harden ingestion and retrieval workflows
Improve source citation reliability
Build or refine structured red-flag extraction
Improve report generation pipeline
Create internal admin/research tooling
Reduce manual work in the current reporting process
Establish QA process for AI outputs
Days 61–90 — Productize
Launch a cleaner MVP workflow for paying/reviewing users
Build investor/customer demo environment
Add repeatable dashboard/report modules
Define scalable architecture for SaaS
Prepare technical materials for fundraising, enterprise diligence, and customer onboarding

Must-Have Background

The ideal candidate has experience with most of the following:

Python
Backend systems
API design
LLM applications
RAG pipelines
Vector databases / embeddings
Structured data extraction
Financial or regulatory data
SEC filings or document-heavy workflows
Cloud infrastructure, preferably AWS
PostgreSQL / TimescaleDB or similar
Data pipelines
Secure multi-tenant SaaS architecture
AI output evaluation and QA
Building MVPs fast without creating garbage
Nice to have 

FinTech experience
Hedge fund / market data experience
Forensic accounting exposure
Short-selling research familiarity
Experience with EDGAR / XBRL
Experience building analyst tools
Experience with agentic workflows
Experience with citation-backed AI outputs
Security / compliance mindset
Prior startup CTO or founding engineer experience

We need someone who can build, reason, simplify, and move.