UUnimatch Lab69
Head of EngineeringУдалённоheadKey responsibilities Engineering system across the holding Own how the holding builds and ships: you are the single technical gate for technical leads, product CTOs, engineers, and infrastructure Stand up the development system for the first year: planning, backlog, reporting, and metrics, so delivery is transparent and forecastable Make the same workflow usable by any product in the portfolio, not a one-off process for a single team Keep dozens of parallel streams in control: prioritize, track, and close them to a result without losing the helicopter view Team, org, and compensation Build the engineering organization from the current base: hire, structure squads and cross-functional teams, and set who owns what Design and run the compensation model for engineering so it matches holding scale, not a single-product startup Run daily management and tracking: what is in flight, what is blocked, what ships, what waits Shape the org so the team can grow without you managing every thread by hand Standards and technical judgment Set shared engineering standards for all products in the portfolio and keep them in use, including how work is planned, reviewed, and shipped Decide architecture trade-offs at holding level: stack, patterns, constraints of hardware, memory, and model architecture, not only LLM tooling Unblock production problems yourself when the system needs it: prototype, Kubernetes, debug, ship AI-agent orchestration Take the AI-agent orchestration architecture the holding runs on from design to production Own the engineering of agent pipelines, harnesses, and wrappers as a production system, not a research demo Required qualifications Experience building and running engineering at scale: tens of people and several products, including from scratch Deep AI background: LLMs, AI-pipeline orchestration, architectures and their limits (hardware, memory, transformer math, RL); background from DevOps through ML Full startup cycle: idea -> PMF -> rounds -> growth STEM or engineering degree Fluent English Already in the United States, or ready to relocate soon Can hold many parallel streams, work with large data, and still ship hands-on (prototype, Kubernetes, production debug) Organizational management, daily tracking, and hiring: strong engineers choose to work with you; you think in product and business, not only in code Preferred qualifications Big-tech experience Hardware and devices; deep work in TTS/STT and conversational AI Agent harnesses, wrappers, and orchestration of AI agents Startup path through IPO Top-tier university Technology stack LLM, transformer architectures, RL AI-pipeline and AI-agent orchestration Constraints at hardware, memory, and architecture level Kubernetes and production infrastructure DevOps through ML Employment terms Format: Full-time, remote; sync windows by agreement (CET and other zones as needed) Location: Europe, MENA, LATAM, USA Compensation: Up to 15000 USDT total (base fix + shipment bonuses) Equity: Option or equity in products you create and lead Venture studio: Option to launch your own startup inside the venture studio - with our infrastructure, team, funding, and network Network: Work with top venture funds from Silicon Valley and a strong professional team AI exposure: Portfolio of AI products in production; regular exposure to leading AI solutions shipped to production APPLY