About usReplicats is building AI-powered autonomous investment agents that bring institutional-grade portfolio management to everyone. Our architecture combines advanced quant models (Black-Litterman, HRP), real-time data processing, smart contract vaults, and conversational LLMs into a scalable platform capable of running 100k+ agents in parallel. We are moving fast — from closed Beta to global rollout — and need a technical leader who can own backend and data infra at scale.The RoleWe’re looking for a Principal Engineer with deep expertise in data and backend systems to architect, optimize, and scale the Replicats core infrastructure. You’ll be hands-on designing resilient data pipelines, ensuring our quant models and LLMs run seamlessly in production, and building the backend services that power autonomous investment agents. You’ll also be a multiplier — raising engineering standards, mentoring the team, and making foundational decisions that shape the product.ResponsibilitiesOwn design and implementation of real-time data pipelines (market data, user interactions, agent logs) with low-latency and fault tolerance.Architect backend services powering agent orchestration, portfolio optimization, and execution.Optimize performance and cost efficiency across distributed systems running at scale.Work closely with quant researchers and AI/LLM engineers to deploy trading algos and integrate them into the platform.Collaborate with smart contract engineers to ensure vault and execution layers are tightly integrated with backend systems.Define best practices in CI/CD, observability, and system reliability.Mentor engineers and set the technical direction for backend and data systems.Requirements7+ years of experience in backend and data engineering.Strong experience in distributed data processing (e.g., Flink, Kafka, Spark) and real-time streaming systems.Proven track record of building and scaling microservice architectures (Python/FastAPI, Go, or similar).Deep understanding of database systems (SQL and NoSQL) and data modeling for high-throughput environments.Experience deploying and monitoring ML/quant models in production.Comfort working in high-ambiguity startup environments and making architectural bets.Bonus: experience with blockchain integrations, financial data systems, or LLM-driven products.Why Join UsWork at the intersection of AI, finance and blockchain.Own the hardest technical problems in a system designed to scale from thousands to hundreds of thousands of autonomous agents.Be part of a founding team, moving fast to define a new category: AI Wealth Management.Below market salary with huge equity potential.