pubGENIUS is a React.js and Next.js development agency and ad-tech startup. We build websites and apps for clients across the US and Europe, specializing in decentralized finance (DeFi, crypto, NFT, blockchain), fintech, and healthcare, with occasional work in e-commerce and other verticals. Beyond client work, we operate our own high-revenue web product with a website, mobile app, and machine learning systems powering our ad-tech optimization engine. Performance is not a preference here, it is a core requirement. We are looking for a Principal Software Engineer, who will be the technical authority, responsible for all development, architecture decisions, and long-term technical strategy across a website, mobile app, and ML-powered ad-tech optimization systems. This is a full-time independent contractor engagement. You will work hands-on at a senior level where site speed and server performance are core success metrics. You will work directly with stakeholders to set technical direction, remove bottlenecks, and ship production-grade code. Engagement Details: - Type: Full-time independent contractor - Hours: Full-time commitment expected - Location: Remote (US, Canada, UK, Ireland or Netherlands) - Clients: US and Europe - Rate: Competitive, based on experience What You'll Own - End-to-end technical ownership of a high-revenue web platform and mobile app - Architecture design and long-term technical strategy - Server-side rendering pipeline using Node.js, Fastify 5, and React 19 - Data layer across MySQL and BigQuery - GCP infrastructure including Cloud Run, Cloud Build, and Global Load Balancer - Ad-tech integrations including Google Ad Manager, GTM, GTag, and GPT.js - Performance optimization at scale, where every millisecond counts - ML pipeline maintenance and optimization for ad-tech performance

• Build the AI-powered internal platform that every Alaner uses daily to navigate the company, find context, and take action. • Design and ship intelligent agents that automate real organizational workflows: onboarding, knowledge retrieval, performance alignment, decision support. • Push LLMs into production for structured reasoning, agentic task execution, and deep integration with internal tools. • Define the primitives and abstractions of AI-native work, the patterns that scale across every team and every country Alan operates in. • Replace generic tools (HRIS, performance reviews, IAM) with opinionated, Alan-native software that compounds with our culture. • Build and scale our Identity & Access Management (IAM), Privileged Access Management (PAM), and user lifecycle across 25+ systems. • Collaborate with product, design, security and leadership to turn Alan's cultural principles into software that amplifies them.

• Lead and grow an Options Engineering team of around 7 engineers • Bring hands-on experience in systematic options trading, ideally including options market-making, automated quoting, execution, and risk management • Own and evolve an existing Rust-native systematic options trading platform • Provide strong technical direction across trading infrastructure, system design, performance, reliability, and risk controls • Work pragmatically through complex engineering and trading-system challenges • Partner closely with trading, quant, product, risk, and infrastructure stakeholders • Balance technical leadership with people leadership, delivery ownership, and operational discipline

• Build Core Platform Infrastructure: Design, develop, and ship core platform components, including workflow orchestration, third-party integrations, and sandboxed execution environments for AI agents. • Drive End-to-End Experimentation: Own the full lifecycle of rapid experiments (hypothesis → build → measure → iterate) to discover what meaningfully improves engineering velocity. • Maintain High-Quality AI Dev Loops: Leverage AI coding agents to write, refactor, and review code, maintaining the strong abstractions and opinionated architecture required for AI to be effective. • Ground AI in Reality: Act as the technical bridge between experimental AI capabilities and real-world engineering workflows, ensuring our tools solve actual pain points. • Full-Loop Ownership: Operate autonomously to take concepts from 0 to 1, delivering tangible improvements and clear signals on AI workflow efficacy without over-engineering the solution.