Back-end Engineer

Sterling Inspired Staffing.

  • New York
  • 26 days ago

    Highlights

    A fast-growing open-source platform is building a cutting-edge feedback loop for optimizing large language model (LLM) applications turning production data into smarter, faster, and more cost-effective models. Backed by world-class investors with experience supporting industry-defining AI and database platforms, we have the resources and runway to pursue an ambitious, long-term vision.

    Numbers & Facts

    LocationNew York

    Description

    A fast-growing open-source platform is building a cutting-edge feedback loop for optimizing large language model (LLM) applications turning production data into smarter, faster, and more cost-effective models.

    What were building

    • A unified model gateway

    • Real-time feedback and metric collection

    • Tools to optimize prompts, models, and inference strategies

    • Built-in A/B testing and experimentation frameworks

    • Seamless observability and optimization pipelines

    Our platform creates a continuous learning flywheel for LLMs, combining:

    • Inference: One API for all LLMs with near-zero overhead

    • Observability: Feed inference data and feedback directly into your database

    • Optimization: Improve from prompt engineering all the way to fine-tuning and reinforcement learning

    • Experimentation: Native support for routing, fallbacks, and advanced testing setups

    We began building quietly in early 2024, ran a successful technical pilot by mid-year, and launched our open-source project in the fall. Backed by world-class investors with experience supporting industry-defining AI and database platforms, we have the resources and runway to pursue an ambitious, long-term vision.

    The Role

    Were hiring a Founding Member of Technical Staff with deep systems engineering experience (especially in Rust).

    Why not just engineer? Because we want cross-functional builders people who can bridge research and production, infrastructure and experimentation. Our core systems are written in Rust, and the scope of work includes features like inference-time optimizations and advanced experimentation frameworks.

    What We Offer

    • Competitive compensation (salary, equity, benefits)

    • The chance to have most of your work be open-source and highly visible

    • Rapid personal growth across both systems and machine learning domains

    • A collaborative, technical, in-person environment where craftsmanship and ambition meet

    • Backing from leading venture funds with experience in AI, infrastructure, and developer tools

    What Were Looking For

    • Strong technical foundation and the ability to drive large projects from start to finish

    • Background in back-end systems and infrastructure (especially with Rust)

    • Hunger for personal and professional growth there are no limits here

    • Willingness to work on-site in NYC with a small, highly focused team


    Package Details

    Competitive compensation (salary, equity, benefits)

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