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Role Description We’re looking for a passionate Backend Developer to join our growing engineering team. You'll be working on scalable backend systems, collaborating with cross-functional teams, and shipping real products used by thousands of users. You build and extend the pricing and matching core — the product's IP. - Pricing engine: Implement the coupled simplex maker from a precise spec: - The three probabilities as a single log-odds vector q = (q_KTL, q_TIE, q_GTL), with prices as p = softmax(q) so they sum to 1 automatically and no buy-all / sell-all arbitrage exists. - A flow nudge (δ = 0.05) that shifts an outcome's log-odds on filled flow, with the softmax coupling automatically lowering the other two outcomes in proportion. - A model/flow blend q_blend = w·q_model + (1 - w)·q_flow−, where the weight w ∈ [0.25, 0.92] drops toward observed flow when a per-outcome imbalance crosses the toxicity threshold (tox_thresh = 0.6). - A dynamic half-spread that widens with toxicity (base 6.5¢, up to 16.25¢) and hard price clamps (floor 3¢, ceiling 97¢), with a 10,000-share hard cap per trade. - The workbook's four no-arbitrage checks wired as runtime assertions that halt the market and page on-call when violated. - Matching tiers (the documented build order): - Tier 1 — direct FIFO matching (same outcome, same YES/NO, opposite side): zero maker risk, peer-to-peer. - Tier 2 — intra-synthetic matching (YES_X ↔ NO_X economic equivalents): closes intra-outcome flow book-to-book. - Tier 3 — cross-outcome hedge matching, hedge-aware and L2-strict: pairs cross-outcome orders only when the pairing strictly reduces the maker's L2 norm. - Maker-risk mechanisms that run alongside matching: - Partial-fill throttle — binary-search the largest fill that keeps L2 at or below the exposure cap; this is the system's non-negotiable safety net. - Whale splitting (500-share chunks) — the single highest-leverage feature on cancel rate and revenue; each chunk runs the full pipeline so maker depth builds between chunks. - Maker auto-quotes — self-unwinding _pPost-tagged ladders ([100, 150, 200]) posted on the unwinding side when |position| > 80. - Mean-reversion / proactive unwinding with accelerated decay (scaling from a 7% base toward a 25% cap as exposure grows) and inventory skew and a book-depth incentive (rest/maker split that gets aggressive when a book is thin). - You’ll measure everything the way the report does — cancel rate, U (residual maker absorption), peak L2, and peak/1K — and reproduce the source exactly: Excel pricing-row parity, the six shock scenarios, the 24 whale round-trips (the whale loses every config), and the 50×50 simulation metric envelope, all green in CI. A central, explicit unknown is adverse selection: the simulations used random traders, and the live market is the first encounter with price-responsive humans — laddered quotes can telegraph maker exposure, and the documented safe fallback is to keep accelerated decay and revert to a single unwind quote. Qualifications - Strong fit: quantitative / market-microstructure background, numerical-precision instincts, comfort turning a mathematical spec into deterministic, test-covered code. - Solid backend engineering in TypeScript / Node.js (or strong adjacent experience and the appetite to be fully productive in TS — the whole stack is one language, with shared types across engine, API, and frontend). - Comfort working from a written spec with test vectors and a habit of proving correctness with tests rather than asserting it. - Experience with PostgreSQL and event-driven architectures; an understanding of why determinism, idempotency, and append-only logs matter here. - A bias toward fail-safe design: when something is wrong, stop — never continue wrongly. Requirements - Prior work on an exchange, order book, trading, betting, or payments system. - Quantitative / market-microstructure exposure, market-maker inventory-risk models, or numerical optimization. - Production WebSocket / streaming experience at scale, NATS or Kafka. - Double-entry accounting or ledger-system experience. - Familiarity with AWS (EKS, RDS), Redis, and Datadog/Sentry observability. Benefits - In addition to a market competitive compensation, we have a reward philosophy that expands beyond this. - Fully remote. - Opportunity to work with a truly global team. - Flexible timings. You decide your work schedule.

• Work within an Agile development team to develop, test and maintain, full-stack web application built on Microsoft technologies for backend hosted on AWS • Attend daily scrum meetings to collaborate with cross-functional teams to identify and solve complex problems and strive for excellent development practice • Develop software applications using .NET C# language and React frameworks with typescript • Work closely with CTO, product owner, business analysts, and other developers to ensure that software requirements are met • Deliver high-quality reusable code, with a focus on service reliability and monitoring • Design and develop cloud-native software • Utilisation of current technical best practices such as writing clean, testable code and pair programming

Develop and maintain Azure-based applications, integrate cloud and on-premises services, and optimize performance while ensuring security best practices. Collaborate with teams to deliver technical solutions and contribute to CI/CD processes.