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Profound

AI answer-engine visibility analytics for brands

Member of Technical Staff - Rust Agent Runtime

Backend EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Have at least four years of experience and a strong portfolio or GitHub demonstrating backend or systems design depth.
  • Be proficient in Rust and comfortable owning production services end to end.
  • Have experience with SQL, relational data modeling, and hands-on use of PostgreSQL.
  • Have experience with distributed-systems patterns, including messaging or streaming, retries, idempotency, and backpressure.
  • Be familiar with caching and state systems such as Redis, and real-time delivery using server-sent events or WebSockets.
  • Understand API authentication and authorization, multi-tenancy, and security best practices.
  • Have experience building or operating workflow engines, schedulers, or agent runtimes.
  • Have experience with Postgres row-level security and data governance at scale.
  • Have practical exposure to containerization, continuous integration or continuous delivery, and cloud environments.
  • Have a background integrating external AI or model providers and securing provider configurations.
  • Have experience working with Rust 2024, PostgreSQL, Redis, Kafka or NATS, containers, modern continuous integration or continuous delivery, and real-time streaming to clients.

Responsibilities

  • Build core workflow-engine primitives to orchestrate agents, tools, and dataflows.
  • Own the real-time control plane, including streaming events, reliable job orchestration, idempotency, and replay.
  • Deliver high-leverage systems that turn prototypes into production-grade, scalable workflows.
  • Design and ship Rust-first backend services and clean APIs for creating, executing, and supervising graph or directed acyclic graph workflows.
  • Build reliable job orchestration with blocking, streaming, and fire-and-forget response modes, supported by durable state.
  • Strengthen tenant isolation, security, and access patterns across the platform.
  • Improve runtime behavior, including scheduling, backpressure, timeouts, retries, and idempotency.
  • Evolve schemas and repositories, and own migrations, indexing, and query performance.
  • Instrument systems with meaningful telemetry and improve testing and operational excellence.
  • Partner with product, frontend, and data teams to deliver high-impact features.

About the Company

Profound

AI answer-engine visibility analytics for brands

Profound helps brands understand and improve how they appear in AI answer engines like ChatGPT, Perplexity, and Google AI Overviews. Its product started as an analytics layer for AI search visibility and now includes research and marketing workflows to track competitors, shape content plans, and measure how AI systems recommend products. The platform analyzes AI-generated results and provides workflows that teams use to plan content and assess impact, rather than just traditional SEO tools. Its goal is to help large enterprises own and improve visibility in AI-generated answers, differentiating itself with a focused AEO/GEO approach and a large, growing customer base.

Company size
201-500
Company stage
Series D
Total funding
$334.5M
Headquarters
New York City, New York
Founded
2024

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