Backend/Systems Engineer

webAI•Austin, TX

About The Position

webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI. You’ll build the “small but serious” backend systems that power real-time, privacy-preserving product experiences like identity, sync, encrypted state, messaging/presence, and group conversations without defaulting to a giant, monolithic backend. You’ll think in terms of edge + device + cloud as a single system, and you’ll ship pragmatic, scalable coordination services that keep products fast, reliable, and secure.

Requirements

3–6 years of backend/systems engineering experience (or equivalent impact).
Strong fundamentals in distributed systems: consistency models, replication, idempotency, failure modes, and performance tuning.
Experience building production services in at least one systems-friendly language (e.g., Go, Rust, Java, C++, Python) and comfort reading others.
Familiarity with real-time systems: WebSockets, gRPC streaming, pub/sub, queues, or event-driven architectures.
Experience designing APIs and data models with security and privacy in mind.
Working knowledge of cloud infrastructure (AWS/GCP/Azure), containerization, and CI/CD.

Nice To Haves

Experience with E2EE concepts: key management, envelope encryption, forward secrecy (conceptual), or secure sync patterns.
CRDTs / operational transforms / event sourcing / append-only logs for sync & collaboration.
Experience with presence systems, chat/group membership, and “fan-out” patterns at scale.
Edge computing or hybrid architectures (device + edge + cloud), and performance work on tail latency.
Security mindset: threat modeling, abuse prevention, rate limits, and secure-by-default service design.

Responsibilities

Design and build identity & session systems
Implement auth flows, device registration, key management integrations, token/session lifecycle, and account recovery patterns.
Support multi-device identity and secure device-to-account bindings.
Ship sync and encrypted state primitives
Build APIs and services that enable state sync across devices (event-based or state-based replication).
Partner with client engineers to support end-to-end encrypted (E2EE) state where the server coordinates without needing plaintext access.
Implement lightweight cloud coordination
Create “coordination services,” not “big backend”: rendezvous, discovery, sequencing, fan-out, rate-limits, abuse controls, and reliability tooling.
Prefer minimal durable state and clear boundaries; push logic to the edge/client when appropriate.
Build real-time messaging, presence, and group chat capabilities
Implement reliable messaging pipelines (delivery semantics, retries, ordering strategies, idempotency).
Support presence and group membership (joins/leaves, device fan-out, read receipts/typing signals as needed).
Integrate with pub/sub or streaming systems, and tune for latency.
Edge-aware systems thinking
Design for intermittent connectivity, offline-first behavior, device constraints, and high tail-latency networks.
Make trade-offs explicit: consistency vs availability, ordering vs throughput, durability vs cost.
Operate what you build
Add observability (metrics, tracing, structured logging), define SLOs, and participate in on-call/incident response (lightweight rotation).
Improve reliability: backpressure, load shedding, graceful degradation, and safe rollouts.