Haizelabs

Haizelabs

Staff+ Software Engineer, Backend and Infra

New York, NY · Staff+

H1B sponsorship available$200k-$300kDetected 111 days ago
PythonGoRustDistributed SystemsNoSQLPostgreSQLMongoDBRedisDatabricksAWSGCPAzureCloud PlatformsKubernetesTerraformDatadogMachine LearningNLPLLMsLogisticsResearchMentoring

About the role

  • Staff+ Software Engineer, Backend and Infra Haize Labs takes AI-based applications from proof-of-concept to production.
  • We eliminate risk and improve the reliability of LLM-based applications by haizing them - i.e. rigorously, proactively, and continuously fuzz-testing them.
  • This is an opportunity to directly influence how AI applications are tested, verified, and deployed by everyone from frontier AI labs to massive enterprises across a wide range of industries.

Responsibilities

  • Design and build scalable infrastructure and systems to orchestrate tens of thousands of LLM calls per second, powering functionality like model evaluations, red team attacks, runtime guardrails, and more
  • Collaborate closely with the research team and deploy innovative new models to build industry-leading AI reliability tooling
  • Develop and uphold processes and best practices that reinforce the operational excellence of our team

Requirements

  • Have 7+ years of industry experience, including 3+ years leading large initiatives as an engineer or manager
  • Have strong proficiency in one or more backend programming languages (e.g. Python, Go, Rust)
  • Have a strong understanding of relational and NoSQL databases (we use Postgres, MongoDB, and Redis, among others)
  • Have experience doing applied AI/ML
  • Have experience working on multi-datacenter, cloud-agnostic systems
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Compensation

  • $200,000 - $300,000 annual salary + equity + benefits

Benefits

  • Act as a technical leader across the organization, mentoring top talent and helping set technical direction and vision for the company

Company info

  • At Haize, we're not here to write GPT wrappers or get rich quick off the AI bubble.
  • We're here to solve the hardest problem in AI: making it safe, reliable, and production-ready.
  • Since our company's inception in 2024, we've amassed amazing customers including OpenAI, Anthropic, AI21, and more.
  • We've developed best-in-class tooling for evaluation, dynamic testing, red-teaming, observability, and continuous "robustification" of AI applications.
  • And we're backed + advised by the founders of Cognition, Hugging Face, Weights and Biases, Nous, Etched, Okta, and Replit, as well as C-suite execs from Google, Stripe, Databricks, Robinhood, and more.
  • Our core team is exceptionally well-suited to accomplish our mission.
  • We've turned down opportunities like Stanford PhD programs and Y Combinator in order to pursue this goal, and we have experience doing AI research and engineering at places like Harvard, MIT, Citadel, Datadog, and McKinsey QuantumBlack (to name a few).
  • We can only serve our mission with an incredibly talented and hard-working team, and we hope that includes you.
  • Come to Haize to push yourself, learn fast, experience excellence, grow with each other, and pursue your life's work.
  • making it safe, reliable, and production-ready.
  • Interface directly with customers to understand and address their pain points, design intuitive new user workflows that streamline their journey, and guide them on the evaluation methodology Haize has pioneered
  • We are looking for a talented and experienced backend + infrastructure engineer to help build out our AI reliability platform.
  • You will play a foundational role in designing and driving forward the core technology that puts our cutting-edge AI research in the hands of customers, empowering them to build AI applications that are trustworthy, robust, and ready for production.

Visa & Work Authorization

  • If you are exceptional, we will sponsor.
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This listing is sourced directly from Haizelabs's careers page and normalized into a canonical job model.