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Lead AI Architect
Lead AI ArchitectProp Firm Match Global – FZCO • US
Lead AI Architect

Lead AI Architect

Prop Firm Match Global – FZCO • US
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About Prop Firm Match Global FZCO

Prop Firm Match Global FZCO is the leading platform for discovering, comparing, and selecting proprietary trading firms. We help traders make confident, informed decisions by offering side-by-side comparisons, verified reviews, and data-backed insights from the top prop firms worldwide. Our mission is to bring transparency, access, and clarity to the prop trading space.

Role Mission

Design, own, and scale Prop Firm Match’s AI strategy and architecture end-to-end. This role connects AI, product, and operations : defining where AI creates real leverage, building the underlying platforms, and guiding teams to ship reliable AI-powered features and workflows at scale.

Requirements

Top 6 Performance Objectives

1. Define and align the AI vision & roadmap

  • Map out high-leverage AI opportunities across product, content, operations, and analytics (what to automate, what to augment, what to build into the product).
  • Prioritize opportunities based on ROI, feasibility, and risk (quick wins vs. strategic bets).
  • Create and socialize a 12-month AI roadmap that leadership and key teams are aligned on.
  • Outcome : Clear, documented AI strategy with 3–5 priority streams approved by founders.

2. Architect a scalable AI platform & integration framework

  • Design the core AI platform : data flows, embeddings / vector DBs, model routing, evaluation layer, and monitoring.
  • Integrate providers (OpenAI, Anthropic, HuggingFace, etc.) in a way that avoids lock-in and supports experimentation.
  • Ensure the platform supports both internal workflows and user-facing features (APIs, internal SDKs, or services).
  • Outcome : A reusable AI platform that can power 10+ features / workflows without re-architecting.

    • 3. Ship the first AI-powered product features and internal copilots

  • Identify 2–3 flagship use cases (e.g., smarter firm comparisons, trader guidance, review summarization, internal decision copilots).
  • Work with Product, Growth, and Ops to define user stories, data needs, and success metrics.
  • Lead the design and implementation—from prototype to production—ensuring reliability, guardrails, and measurable impact.
  • Outcome : At least 2 AI-powered features live with clear uplift in key metrics (conversion, engagement, time-to-insight, etc.).

    • 4. Set reliability, observability, and governance standards for AI systems

  • Establish standards for logging, monitoring, evaluation, and rollback for all AI and automation systems.
  • Implement dashboards for model performance, drift, latency, and error rates.
  • Define basic AI governance : data privacy rules, safe use patterns, human-in-the-loop where needed.
  • Outcome : No “black box” AI — every system is observable, explainable internally, and safe enough to run at scale.

    • 5. Turn vague business ideas into robust, documented AI / automation solutions (ongoing)

  • Partner with non-technical stakeholders to run discovery : what outcome do we want, what inputs / outputs exist, where are the constraints.
  • Translate this into clear architecture specs and implementation plans that teams can understand.
  • Deliver fast MVPs, then mature them into resilient systems with proper error-handling, testing, and documentation.
  • Outcome : Stakeholders consistently experience that “we had a fuzzy idea → now we have a working AI system that clearly adds value”.

    • 6. Build and mentor a small AI & automation function

  • Define roles needed (e.g., AI Automation Engineer, ML / AI Engineer, Analytics / AI bridge roles).
  • Hire or upskill 1–2 contributors and set standards for code quality, design, experimentation, and documentation.
  • Coach engineers and non-technical staff on what “good AI / automation” looks like and how to work with the platform.
  • Outcome : A lean, high-leverage AI function where the Lead Architect is less of a bottleneck and more of a force multiplier.

    • Must-Have Profile (Outcome-Linked)

    Candidates should be able to demonstrate past accomplishments like :

  • Owning AI strategy + architecture for a product or internal platform (not just “built a model once”).
  • Designing a reusable AI or automation platform (inference pipelines, vector DBs, monitoring, evaluation).
  • Shipping production AI features used by real users / teams, with visible business impact.
  • Working fluently with LLMs + vector search + APIs, and making pragmatic trade-offs between options.
  • Turning half-defined ideas (“we should use AI here”) into a concrete architecture and successful delivery.
  • Collaborating with Product, Growth, and Ops, not just engineering.
  • Mentoring others and setting technical standards.

    • Soft Skills / Leadership

  • Thinks in systems , not isolated tools.
  • Habitually asks : “What outcome are we trying to create?” before touching tech.
  • Calm, methodical, and reliable under ambiguity and moving targets.
  • High bar for quality : testing, logging, documentation, reproducibility.
  • Strong written and verbal communication; can explain architecture and trade-offs to non-technical leaders.
  • Natural mentor; leaves things better structured than they found them.

    • Benefits

    Why Join Prop Firm Match Global FZCO?

    ▸  Contribute to a growing platform shaping the future of proprietary trading

    ▸  Work within a flat, collaborative team where your input is valued

    ▸  Competitive compensation, including base pay and benefits

    ▸  100% medical, dental, and vision coverage (U.S. only), including gender-affirming care

    ▸  Flexible PTO including sick time, holidays, refresh days, and sabbatical leave after five years

    ▸  Work remotely with the flexibility you need to maintain balance and focus.

    ▸  A professional, transparent, and healthy work environment that values both results and people.

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