• Design and build scalable backend systems powering Veda’s API and internal services • Own projects end-to-end — from scoping and design to implementation, testing, and production delivery • Collaborate with product and infrastructure teams to turn technical debt into modern, maintainable, and highly available systems • Write clean, well-tested code, and maintain strong CI/CD hygiene • Deploy, monitor, and scale services in production using modern cloud tooling (AWS, GCP, or similar) • Contribute to system design discussions covering performance, reliability, and data architecture • Participate in on-call rotations and incident response for production systems • Continuously identify and drive improvements in system reliability, observability, and performance

• You will build the backend systems that make Alaro’s product reliable, extensible, and safe to use in real legal work. • These systems power everything lawyers see and trust: documents, matters, permissions, agent actions, and the workflows that tie them together. • At a high level, we are building a Cursor-like environment for legal work, where lawyers collaborate with agents that can search, reason, and act on documents, while remaining auditable, reversible, and correct. • This is a product-first backend engineering role. To succeed, you’ll need to understand the full product surface and agent behavior, so you can design systems that evolve quickly without breaking under real-world usage. • Core product APIs: design and evolve the APIs that power the lawyer dashboard: matters, documents, chats, permissions, and email integration, so legal work stays coherent across tools, collaborators, and time. • Data models and pipelines: define and maintain data structures that support evolving product and agent workflows, including document state, provenance, permissions, and history. You’ll think carefully about boundaries, migrations, and long-term extensibility. • Agent-facing backend surfaces: build the primitives that let agents safely operate in the system: scoped permissions, state transitions, execution boundaries, and backend objects that unlock new tools and workflows without sacrificing control. • Infrastructure and reliability: own backend systems in production. Contribute to deployments, observability, performance, and cost awareness, while keeping the focus on product reliability rather than infrastructure for its own sake.

• Join our core engineering team, responsible for backend development of AI Agent products • Help build our open-source community and ecosystem around the models and products • Work with top researchers, optimizing model evaluation frameworks from the engineering side • Build data flywheels, and improving model performance

• Own the architecture and technical direction of high-performance trading APIs (HTTP & WebSocket) supporting low-latency order entry, market data distribution, and account state updates. • Lead the design and implementation of structured concurrency using the Tokio runtime, defining best practices for task lifecycle management, cancellation semantics, backpressure, and graceful degradation under load. • Develop and maintain real-time state ingestion pipelines: Process append-only logs (e.g., trades, order updates, book diffs) and rebuild local states efficiently using snapshot + diff application. • Model trading-related data structures, including orders, fills, trades, positions, funding, and liquidation logic. • Implement WebSocket connection logic, including upgrade handling, frame parsing, and data fanout for subscribed clients. • Design observable backend systems with rich metrics, structured logging, and distributed tracing for performance insights and failure analysis. • Collaborate with system and infrastructure engineers to continuously improve performance, scalability, and fault tolerance. • Write comprehensive unit, integration, and load tests to ensure stability under production conditions.