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Mid-level AI role in a metro YC-backed startup with generalist ML requirements increases competition.
LLM, voice, and production ML skills transfer across industries, though fintech domain knowledge helps.
Explicit 2–5 years plus mandatory Python and production ML/LLM experience makes screening moderately strict.
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Own development of the multi-turn autonomous AI voice agents handling payment negotiations, compliance, and objection handling in financial conversations.
Build and maintain real-time voice AI systems with sub-1s latency, including speech model integration, voice activity detection, and WebRTC stream debugging.
Develop and refine LLM orchestration, prompt engineering, and evaluation frameworks to ensure conversational quality, empathy, and compliance.
2-5 years of hands-on engineering experience, including working with ML or AI systems in production.
Strong proficiency in Python with ability to write clean, maintainable code and debug production issues.
Experience with LLMs such as prompt engineering, API integrations, or building pipelines/agents.
Work Experience Required: 2-5 years; Notice Period: Not explicitly mentioned in the JD.
Engineer comfortable taking ownership of complete features and components with a strong bias for action and shipping rather than over-engineering.
Experience or interest in voice AI (speech-to-text, text-to-speech), real-time infrastructure, or low-latency systems to handle conversational AI pipelines.
Familiarity with fintech, lending, or collections domain, or with building or tinkering agentic systems combining LLM reasoning and structured actions.