Builder Block

Role:  Principal Platform Builder (FTE – Permanent)

Location:  100% remote (the selected candidate will have the opportunity to work their own “local hours”)

Candidate location preference:  Strong preference will be toward EU or CEE-based candidates, but other locations will be considered.

Come help build the prototype-to-market path of E-TIE, RudieSec’s external threat intelligence engine.  This is an internal platform for external CTI and OSINT.  It processes outside-the-firewall threat intelligence and supports client-facing cybersecurity recommendations, along with business operations justifications.

What you’ll be building:

The selected candidate will build the first full-stack, code-based version of E-TIE by translating a validated v1.block1+ prototype into a maintainable platform where the back-end engine and interfaces evolve together.  Once the initial prototype moves into production, further platform iteration will be driven by the external threat environment (we need to revise as the environment activities shift, within reason), and client threat intelligence needs evolve.  This role is not a “build & manage tickets” role, rather it is a Kanban, continual improvement-based “build, revise, build…” role.

Key build elements include: 

A Python-first core on Linux in AWS, a clean data model and service boundaries, a coded reference implementation matching prototype outputs with tests and logging, and workflow-supporting interfaces (dashboards, review views, stateful forms, etc.).

Integration-ready by design:

Build clean APIs and modular connections for third-party intel sharing and evidence-grade artifact libraries, while keeping E-TIE’s core analytic functions independent of any external integrations.

Current state and near-term build targets:

E-TIE currently exists as a v1.block1+ reference prototype.  The near-term objective is to deliver a working coded system that reliably matches reference behavior, then lay the foundation for expansion without breaking core behaviors.

Skill and technical requirements:

Must-haves:

• Full-stack capability, strong Python, Linux comfort, practical AWS experience, ability to design APIs and data models, engineering discipline (tests, logging, secure coding, documentation [yes, we know…boring, but it must be done]), comfort shipping iteratively (Agile) with ownership.

Nice-to-haves: 

• Workflow-heavy UI experience, analytics-adjacent systems familiarity, CTI context exposure (strongly preferred, but we can build up on the basics here).

Indicators of Interest:

To indicate your interest in the Principal Platform Builder role, please complete the contact form:  RudieSec TA. 

Please follow these instructions for submitting:

• Put “RudieBuilder” in the Subject line of the email
• Provide a 1-3 paragraph intro.  Just tell us who you are, what excites you about building and programming, and what piques your interest in joining a cyber threat intel startup.  Relax, be genuine, and explain it to us as you would to a colleague.  Note:  Please do not submit your CV or build portfolio yet.
• LinkedIn profile link
• Preferred contact info

Role:  Principal Math Modeler (FTE – Permanent)

Location:  100% remote (the selected candidate will have the opportunity to work their own “local hours”)

Candidate location preference:  Strong preference will be toward EU or CEE-based candidates, but other locations will be considered.

Education requirements:  Bachelor’s degree or higher in a quantitative field (statistics, mathematics, computer science, engineering, economics, or similar), or equivalent real-world experience demonstrating strong modeling capabilities.

Come help build the prototype-to-market path of E-TIE, RudieSec’s external threat intelligence engine.  This is an internal platform for external CTI and OSINT.   E-TIE treats the outside-the-firewall environment as an intelligence arena, not just a technical one.  If you like turning messy real-world signals into measured, defensible intel outputs, this role is for you.

What you’ll be building:

The selected candidate will own the work of our quantitative and time-series modeling direction across E-TIE’s analytic layers, with heavy emphasis on clarity, evaluation, and operational usefulness.  Our prototype-to-production + path will include a Kanban, continuous improvement-based process that evolves as the threat environment shifts and client requirements grow.  Iterative modeling will be the norm.

Core responsibilities include:

• Markov quantitative/predictive layer:  define state logic, transitions, scoring, and how probability shifts as intelligence accumulates (including guardrails for over-fitting and noise).
• Forecasting layer (Chronos-2, planned):  define what “forecasting success” means in this domain, specify evaluation methods, and shape integration requirements so that forecasts become testable and decision-relevant for our clients.
• Statistical and reporting layer (R or equivalent):  define how outputs should be expressed so that uncertainty, confidence, and model performance are visible and explainable.

Evaluation mindset:

This role is not “build a clever model, and vibes will carry it.”  We want disciplined measurement:

• Define validation and backtesting expectations.
• Establish error metrics and boundary checks.
• Specify what qualifies as “minimal acceptable signal threshold” for state transition updates, time-based half-life regression and recursion, and confidence-based regression and recursion.
• Help design monitoring signals for environmental drift and degradation over time.

Integration-ready by design:

E-TIE will support third-party integration (for intel sharing and evidence-grade artifact libraries).  The selected candidate’s modeling work should assume external data can enrich the system, but must remain robust when those integrations are absent.  Integrations should improve coverage and confidence, not become a hidden dependency.

How you’ll work:

The selected candidate will collaborate closely with the Principal Platform Builder to ensure model logic is implementable, testable, and maintainable.  You’ll also help translate analytic outputs into forms that a SOG Analyst can use to drive defensible client recommendations.

Skills and technical requirements:

Must-haves:

• Strong applied quantitative judgment.
• Comfort with Markov modeling concepts and time-series forecasting fundamentals.
• Evaluation mindset (calibration, backtesting, and measurable performance).
• Ability to translate modeling logic into implementable requirements (Python familiarity strongly preferred).
• Clear communication of assumptions and uncertainty.

Nice-to-haves:

• Bayesian methods, HMMs, calibration techniques.
• Model monitoring experience (drift, regression, recursion, performance decay).
• Experience in adversarial domains (cyber, fraud, risk, intelligence, etc.).

Indicators of Interest:

To indicate your interest in the Principal Math Modeler role, please fill out our contact form:  RudieSec TA. 

Please follow these instructions for submitting:

• Put “RudieMath” in the Subject line of the email
• Provide a 1-3 paragraph intro.  Just tell us who you are, what excites you about building real-world applications of math models, and what piques your interest in joining a cyber threat intel startup.  Relax, be genuine, and explain it to us as you would a colleague.  Note:  Please do not submit your CV or build portfolio yet.
• LinkedIn profile link
• Preferred contact info