Sky is transforming from a crypto bank into a crypto central bank. We no longer allocate the collateral portfolio directly. We lend to independent allocators, called Prime Agents, who deploy capital across DeFi and RWAs. Your mandate is to help design and iterate the risk engine that keeps Sky safe and protects the USDS peg while letting Primes move fast and win.
This is a builder role for someone who is hungry for outsized impact and upside. Think the New York Fed for a crypto-first, post-Singularity world. If you want to invent robust models, codify them into capital and liquidity policy, pressure‑test them in fast decision forums, and see billions move because of your work … read on.
Atlas Axis serves as Core Council GovOps for Sky, acting as the main governance actor for Sky on a day to day basis. In this role we develop the Atlas, the comprehensive body of rules that define how actors in the Sky Ecosystem interact with each other. One of our main focuses is helping to develop the risk framework that governs all allocators in the ecosystem. As Risk Lead, you will own this workstream and help our team to develop an independent point of view on all risk matters. Your success will be measured not only against the resilience of the Sky risk framework, but also against our team’s ability to contribute substantively as an independent, trusted risk stakeholder.
You'll help build the foundational risk and governance infrastructure that enables Sky to scale from a handful of independent allocators to hundreds.
You'll work at the cutting edge of DeFi, rapidly learning novel crypto primitives with zero historical precedent and translating qualitative unknowns into quantitative risk parameters. You’ll make discretionary decisions that don’t fit within the existing body of rules, especially in the short term. This might include whether an investment in a novel opportunity should be allowed at all, how much capital should be required for a new opportunity, or how Sky level risk considerations should flow down to limits for particular allocators.
Your work will span multiple pillars:
Capital: set portfolio‑level and product‑level capital buffers that scale across asset classes
Liquidity: defend the USDS peg. Define what counts as immediately‑usable vs. quickly‑convertible liquidity and how it supports redemptions and rate policy.
Technical/operational: craft scalable frameworks for smart‑contract, admin, and process risk so novel deployments are enabled safely.
You’ll collaborate in a fast decision cadence with protocol engineers, risk partners, legal, and capital allocators. You’ll navigate high-stakes disagreement in real-time decision forums where allocators and colleagues push back on your assumptions and data.
Illustrative work you’ll own in your first 90 days
Build operational tooling for our lending markets capital model (Basel‑inspired, adapted to DeFi), including calculators, worked validation examples, and sensitivity analyses.
Introduce interim, liquidity‑aware parameter templates (e.g., exposure tiers with rate add‑ons that scale with market depth), guide them through adoption and develop validation criteria for when to replace them with systematic frameworks.
Propose peg-stability buffers (immediately-liquid vs. convertible assets) with stress scenarios and clear triggers for intervention.
General categories
Build models
Convert qualitative risks (governance privileges, bridge trust assumptions, protocol maturity) into quantitative capital requirements with clear reasoning
Design capital models per asset class: Lending markets; Bond‑like instruments (PTs); Perpetual Strategies; Real‑World Assets (RWAs); and Cash Stablecoins.
Incorporate market, credit, and liquidity risk factors; account for smart‑contract, administrative/governance, and operational risks with practical limits.
Stress test liquidity under adverse scenarios (bank runs, market panics, bridge failures); define gates for scaling liquidity requirements and rate adjustments.
Codify decisions into governance proposals, monitoring dashboards, and automated enforcement where possible.
Monitor live allocations, run post‑mortems. Systematically update models when reality diverges from assumptions; refine parameters as data arrives. Build feedback loops that turn operational experience into better frameworks.
Illustrative work you’ll own in your first 90 days
Build operational tooling for our lending markets capital model (Basel‑inspired, adapted to DeFi), including calculators, worked validation examples, and sensitivity analyses.
Introduce interim, liquidity‑aware parameter templates (e.g., exposure tiers with rate add‑ons that scale with market depth), guide them through adoption and develop validation criteria for when to replace them with systematic frameworks.
Propose peg-stability buffers (immediately-liquid vs. convertible assets) with stress scenarios and clear triggers for intervention.
General categories
Build models
Convert qualitative risks (governance privileges, bridge trust assumptions, protocol maturity) into quantitative capital requirements with clear reasoning
Design capital models per asset class: Lending markets; Bond‑like instruments (PTs); Perpetual Strategies; Real‑World Assets (RWAs); and Cash Stablecoins.
Incorporate market, credit, and liquidity risk factors; account for smart‑contract, administrative/governance, and operational risks with practical limits.
Stress test liquidity under adverse scenarios (bank runs, market panics, bridge failures); define gates for scaling liquidity requirements and rate adjustments.
Codify decisions into governance proposals, monitoring dashboards, and automated enforcement where possible.
Monitor live allocations, run post‑mortems. Systematically update models when reality diverges from assumptions; refine parameters as data arrives. Build feedback loops that turn operational experience into better frameworks.
Blue‑chip TradFi pedigree plus crypto: hedge fund, investment banking, or asset‑management experience, combined with DeFi chops is our ideal profile. You understand traditional finance well enough to see its fundamental limitations - and you're motivated to build the infrastructure that replaces it.
Crypto asset‑management or trading‑ops profiles who authored risk frameworks/guidelines for capital allocators are highly relevant.
Active trading/investing mindset.
Risk roles inside finance firms can work if you’ve built new models under ambiguity. You're comfortable setting a number today knowing it's imperfect, documenting why, and committing to improve it as data arrives.
You’re not intimidated by organizational friction: allocators who resist limits, incomplete data, and pressure to approve deals faster than frameworks mature.
As much as you know the numbers, you know numbers aren’t everything. You know how to incorporate qualitative factors and on the ground realities of a situation as well.
We are building a system that needs to be able to scale to hundreds or thousands of allocators. You think not just about the right result is in this case but how that result will contribute to achieving an end state where we are infinitely scaleable.
You are using AI daily in your workflows. You love to cook up innovative ways to use AI to augment intelligence - data gathering, analysis, modeling, coding, etc.
Deep quantitative toolkit: strong Excel and Python/SQL; can build cohort analyses, simulations, and stress tests from raw chain and market data.
DeFi native: hands‑on with lending markets, basis/perp structures, and stablecoin/liquidity mechanics across EVM and other chains including Solana.
Risk modeling fluency: Basel‑style capital, liquidity coverage, drawdown/vol surfaces, and portfolio aggregation.
Exceptional communicator: clear writing for Atlas edits and public communications; clear speaking as our team’s risk representative. You understand how essential it is to develop shared context, and you’re patient and keen to wrap complex concepts in accessible language.
High‑bandwidth async collaboration.
Full integration of AI into your toolbox.
Deep into Solana DeFi ecosystem (or ability to quickly acclimate)
A big plus: experience authoring policy in on‑chain governance systems; prior central‑bank/ALM exposure
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