M
AI Engineer
Marco Russo
Full-time · Mid-level · Los_Angeles
About the role
Context: we serve 1.2 million users. Our AI features handle 300,000 requests per day. Our P95 latency for LLM calls is currently 4.2 seconds. Our target is 1.8 seconds. We have a hypothesis about where the bottleneck is. We need an AI engineer who can test that hypothesis, implement the fix, and own the performance monitoring layer going forward. Direct impact. Measurable output. Clear success criteria from day one.
Responsibilities
- Profile and diagnose current AI feature latency bottlenecks
- Implement streaming responses and caching strategies
- Build latency and cost dashboards for the AI features layer
- Own the LLM API integration layer and keep it efficient
- Document all performance improvements with before/after benchmarks
Requirements
- 2–4 years building AI features with LLM APIs in production
- Experience optimising LLM call latency (streaming, caching, prompt compression)
- Strong Python with async programming experience
- Familiarity with observability tools (Datadog, Grafana, or similar)
- Able to scope and deliver a performance improvement project independently
Benefits
- Concrete problem with measurable success criteria
- Full remote
- $95,000 – $125,000
- Equity package
- Engineering-first culture — no endless meetings
Job Type
Full-time
Level
Mid-level
Language
English
Salary Range
$95,000 – $125,000
AI Expertise
AI & Machine Learning Engineers
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