• Desarrollar y mantener componentes web reutilizables utilizando JavaScript, Web Components y lit-element. • Implementar interfaces de usuario escalables y accesibles con HTML y CSS. • Integrar aplicaciones frontend con servicios backend mediante llamadas a APIs. • Gestionar versiones y flujos de desarrollo utilizando git y npm. • Realizar y mantener pruebas unitarias asegurando calidad y rendimiento. • Colaborar en entornos Agile junto a equipos multidisciplinares.

Role Description Our client is a high-growth technology firm. They are seeking a Staff Software Engineer to spearhead two critical domains: the core agent runtime and backend infrastructure powering a high-frequency trading fleet, and the comprehensive migration of model hosting and agent deployment to in-house, proprietary infrastructure. This is a foundational, high-impact building role. The successful candidate will design and implement the backend services, runtime engines, and deployment systems that enable a fleet of autonomous agents to operate with superior speed, reliability, and intelligence. By moving away from third-party LLM providers and hosted platforms, this role will establish the sovereign infrastructure necessary for the next generation of autonomous financial software. Key Responsibilities - Agent Runtime & Backend Development - Plugin Runtime Ownership: Lead the evolution of the per-agent process, migrating from a distributed Go/Python hybrid to a centralized, high-performance Go service utilizing Postgres state and real-time websocket price feeds. - Rules Engine Engineering: Build a YAML-configurable "Scanner Gateway" to bridge signal production and execution, allowing for complex scoring and filtering without direct code manipulation. - Advanced Execution Systems: Develop and maintain the RatchetStop Backend, a centralized profit-trailing service capable of sub-second evaluation and websocket-based order execution to protect capital even when agents are offline. - Data & Connectivity: Manage the Model Context Protocol (MCP) server bridging agents to platform tools, and oversee a high-throughput data pipeline (Redis, Postgres, ClickHouse) for real-time market intelligence ingestion. - Model & Agent Hosting Migration - Infrastructure Sovereignty: Lead the technical execution of migrating agents from third-party platforms to a custom-built, Senpi-hosted environment featuring isolated workspaces and state persistence. - Model Serving: Evaluate and implement the transition from external LLM APIs (Anthropic, Google) to self-hosted inference, optimizing for telemetry capture and performance. - Telemetry & Feedback Loops: Architect systems to capture every agent decision and score, creating a self-reinforcing loop where the fleet learns and improves from collective performance data. - Deployment Pipelines: Build robust CI/CD pipelines for zero-downtime rollouts, ensuring that updates to scanner logic or runtime patches do not interrupt active market positions. - Infrastructure & Operations - System Reliability: Design monitoring and alerting frameworks to detect agent failures, state corruption, or authentication expirations before they impact financial performance. - Cloud Orchestration: Manage AWS/EKS environments using Infrastructure-as-Code (IaC). - Incident Response: Own the operational health of the fleet, acting as the primary responder for high-stakes trading system incidents. Interview Process - Founder / CEO Interview: Introduction to the vision and strategic goals. - Take-Home Test: A practical assessment of technical design and coding capabilities. - Technical Interview: A deep dive into systems architecture and engineering expertise. - Final Interview: Cultural alignment and final technical synthesis. Technical Essentials - Expert Backend Engineering: Proficiency in writing production-grade code in Go, Python, and Node.js/TypeScript (Go is strongly preferred for runtime services). - Startup Experience: A proven track record of building complex backend services (APIs, job scheduling, distributed systems) from scratch in a fast-paced environment. - Real-Time Systems: Deep understanding of low-latency environments, websocket management, and sub-second condition evaluation. - Database Mastery: Production experience with Postgres, Redis, and at least one analytical database (e.g., ClickHouse, TimescaleDB, or BigQuery). - Orchestration: Hands-on experience deploying, scaling, and debugging production workloads on Kubernetes (AWS EKS). - End-to-End Ownership: Demonstrated ability to design, build, deploy, and maintain systems throughout their entire lifecycle. Preferred Qualifications - LLM Infrastructure: Experience with model serving and optimizing inference (e.g., vLLM, TGI, or TensorRT-LLM). - FinTech/Trading: Background in exchange APIs, wallet operations, or on-chain infrastructure where uptime has direct financial consequences. - Agentic Frameworks: Familiarity with Model Context Protocol (MCP) or orchestrating multi-agent platforms. Benefits - Competitive compensation and equity packages. - The opportunity to build foundational infrastructure in a new category of autonomous software. - High-autonomy environment with a focus on engineering excellence. - Collaborative culture working alongside industry-leading founders and engineers. Commitment to Equality and Accessibility At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.

Location: Remote Americas preferred location Remote | Full-time Compensation: $150k-$200k base plus equity/token We are hiring on behalf of our our client who is developing a high-performance agent runtime specifically engineered for the Hyperliquid ecosystem. This infrastructure includes hardened execution environments, a proprietary data layer, and an open-source strategy marketplace designed for autonomous AI trading agents. Having already established significant market traction with over 1,100 monthly active trading agents and exceeding $100M in 30-day volume, the organization is now scaling its operations to support tens of thousands of agents. The Head of Growth will be responsible for the end-to-end adoption of these AI agents. This is a 100% performance-driven leadership role where success is measured by concrete metrics: agent deployments, trading volume, and unit economics. The individual in this position will be fully accountable for Customer Acquisition Cost (CAC), Lifetime Value (LTV), and payback periods, moving beyond traditional brand marketing to focus on data-backed growth. Key Responsibilities - Funnel Management: Own the full acquisition funnel, from initial awareness and signup to the first agent deployment and sustained active trading volume. - Channel Execution: Build and execute growth strategies across organic and paid channels, including X, YouTube, Reddit, Coinbase network, Google, and emerging social platforms, with a specific focus on onchain and AI product conversion. - Data-Driven Strategy: Develop content strategies centered around open-source skills, live leaderboards, and arena results, converting real-time trading data into scalable growth engines. - Segment Activation: Identify and activate high-value onchain user segments, including perpetual traders, algorithmic/quantitative traders, DeFi power users, and AI agent developers. - Product Collaboration: Work closely with product and engineering teams to optimize onboarding, retention, and activation flows. - Ecosystem Building: Foster community and developer relations within the strategy ecosystem via GitHub, Discord, Telegram, and strategic partner integrations. - Economic Accountability: Manage CAC/LTV economics by channel; analyze the cost to acquire agent deployers against their lifetime volume and revenue contribution. - Performance Reporting: Track and iterate on growth metrics weekly, ensuring every dollar of spend is defensible through data regarding activation rates and retention curves.

Location: Remote - +/- 3 hours from CET (EST / Europe preferred) Remote | Full-time Compensation: $90K - $150K We are hiring on behalf of our client in the high-growth Web3 and DeFi sector who is seeking a Senior Backend Engineer to join its core Platform team. This organization builds and evolves the distributed backend systems that power its primary products and customer-facing solutions. The successful candidate will design and operate complex systems, manage Web3 infrastructure, and collaborate closely with product and platform engineers to deliver reliable, scalable solutions. This role is ideal for an engineer who values strong ownership, thoughtful system design, and maintains a high bar for code quality. The client fosters an environment that prioritizes building solid systems and moving quickly without compromising standards, leveraging modern tools—including AI—to maximize efficiency. Key Responsibilities: - System Architecture: Design, build, and maintain scalable distributed backend systems powering core platform and product capabilities. - End-to-End Ownership: Manage backend services throughout their entire lifecycle, from initial architecture and implementation to monitoring and long-term reliability. - Product Collaboration: Partner with product and engineering peers to actively shape product decisions and strategy rather than merely executing technical specifications. - Web3 Integration: Build and evolve platform backend components, including protocol integrations, support for emerging blockchain networks, and reliable interactions with smart contracts. - Engineering Standards: Ensure high standards of code quality, performance, security, and observability across all services. - Operational Excellence: Operate effectively in a fast-paced startup environment, balancing development velocity with technical correctness. - Innovation: Leverage AI-assisted tools to improve development velocity and personal productivity while contributing to technical discussions, reviews, and mentorship within the team.