Founding Engineer

3 days ago


San Francisco CA United States Hamming AI Full time

We are a fast-growing voice AI testing company. We are winning (8Xed our revenue last month) and are hiring a founding engineer to help us win faster.

Here's what you'll do:

  1. 0 to 1
    • Build new products extremely quickly that make our customer’s voice agents more reliable. Our customers want new features, and we don’t have enough time to satisfy current demand.
  2. 1 to N
    • Scale current products and infra to support 100x growth. This includes optimizing and productizing processes that humans currently do.

LET’S CHAT IF YOU

  • Are you an ex-founder who is looking to join a hyper-growth startup or were previously a founding engineer at another startup
  • Are a power user of Cursor, Zed, etc., and started using code-gen tools before they went mainstream.
  • Have deep intuition about what the current gen LLMs are capable of and what kind of tasks that are hard now will become easier in the next model.
  • Are fast at 0 to 1, but also thoughtful about how your technical decisions will scale over time.
  • Want to grind with us, staying close to customers to iterate fast and solve their problems.
  • Think independently and do whatever it takes to get things done while maintaining a high-quality bar.
  • Are excited about making AI voice agents reliable.
  • Have shipped production LLM apps that people use.
  • Have built 0-1 real-time systems at scale in Telecom/Networking, Autonomous Vehicles or high-frequency trading.
  • Have hands-on expertise with distributed systems and a knack for orchestration, monitoring, and analytics.

BONUS POINTS

  • Fluent in model-based evals, observability, and prompt optimization work like DSPy.
  • Have built AI voice apps.

TECH STACK

  • Essentials: Next.JS, TypeScript, Python, Tailwind
  • AI: OpenAI, Anthropic, STT, TTS, etc.
  • Infrastructure: PostgreSQL, k8

INTERESTING TECHNICAL CHALLENGES

  • Create voice simulations that model the real world (background noise, accents, etc.)
  • Generalize DSPy style prompt optimization to voice
  • Support 10K parallel calls with 99.99% reliability
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