Role Description This is a unique opportunity to see out and work in developing Ukio's products from very early conception to the final stage. Working 100% remotely you will join a highly skilled, forward-thinking team working in a cross-discipline manner. As a start-up, and with Ukio’s unique culture you can expect an exciting environment, with a lot of room for innovation, new ideas and suggestions. You will work on enhancing our platform to boost efficiency for Ukio teams while enabling an outstanding customer experience. Your contributions will play a key role in streamlining processes and delivering exceptional value to our users. Responsibilities - Build and Innovate: Collaborate with cross-functional teams to design, develop, and deploy features that elevate the Ukio platform. - Drive Automation and Integration: Develop technology that harnesses AI to achieve a high degree of automation and integration, optimizing Ukio’s operations efficiency and enhancing the customer experience. - Ensure Quality: Write clean, maintainable code and participate in code reviews to uphold high standards and best practices. - Solve Problems: Analyze project performance, troubleshoot issues, and optimize systems for scalability and reliability, supported by AI-driven insights. - Collaborate and Communicate: Work closely with product managers, designers, and engineers to identify opportunities and propose impactful solutions. - Understand Our Users: Develop empathy for our users’ needs to deliver intuitive solutions that make city living effortless. - Learn and Grow: Stay curious, experiment with new technologies, and contribute ideas to keep our platform innovative. Qualifications - Experience: 2-3 years as a backend engineer, with hands-on experience in a dynamically typed language (we use Elixir and Phoenix, but similar languages like Python or Ruby are welcome). - Technical Skills: Proficient with SQL and comfortable in AWS environments. Familiarity with AI or automation tools for boosting productivity is a plus. - Problem-Solver: You have a keen eye for detail, love tackling challenges, and can propose well-reasoned technical solutions. - Collaborator: You communicate ideas clearly to technical and non-technical team members, fostering alignment and teamwork. - Adaptable: You thrive in a fast-paced environment, embrace short feedback loops, and are comfortable with ambiguity and change. - Ownership: You’ve led or contributed significantly to engineering initiatives and take pride in delivering high-quality work. - Language: Fluent in English, with strong written and verbal communication skills. - Curious Learner: You’re eager to explore new tools, see AI as an enabler for productivity and innovation, and are driven to stay ahead of the curve. Benefits - Flexible schedule - Fully remote (work from home) - Investment in your learning and development - Private health insurance - Employee Stock Options Plan - UKIO Anniversary gift - A challenging job at one of the fastest growing companies in Europe - Competitive annual gross salary, to be determined in line with your knowledge and experience - International working environment with many different nationalities - Work with talented, committed and supportive teammates - Team events and an amazing internal culture

• Independently guide the technical direction and implementation by the whole team within defined architecture in all stages from conceptualization to deployment. • Evaluate trade-offs between correctness, robustness, performance, and customer impact to ensure the development of the right solution, with client success at the forefront. • Create and lead the team's technical documentation and repository management practices, including tasks such as creating branches, pull requests, merges, etc. • Collaborate with product, design, and engineering teams to provide necessary oversight of architecture and dependencies influencing product strategy and direction. • Contribute to code reviews, documentation, and addressing complex bug fixes with a focus on security, performance, and reliability. • Mentoring Junior Engineers on project teams, supporting the growth of technical capabilities.

• Join a company that empowers you to do your very best work. • Take this challenge and make an impact in your career! • Work with multidisciplinary teams, multiple industries, and projects. • Create easy and intuitive digital products that improve people's lives.

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.