Humans make billions of calls/day. We think a majority of these will be handled by AI built by thousands of companies tackling every single vertical.

Making these AI voice agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs.

Hamming automates testing for AI voice agents. With one click, 1000s of our voice agents call our customer’s voice agents using different accents, tones, cadences, and personalities. For each call, we provide detailed bug reports.

Our revenue grew 8X in the last month.

Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla.

Marius (CTO) previously ran data infrastructure @ Anduril and was a founding engineer @ Spell (MLOps startup acquired by Reddit).

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:

• 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.
• 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 are 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

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