Replicant
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Lead exploration and application of large language models and generative AI for enterprise contact-center automation. Translate research into high-performing, deployable ML systems; contribute across experimentation, implementation, and deployment; collaborate with engineering and product teams; optimize performance; and help shape team strategy, innovation, and professional growth.
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Design, build, and operate customer-specific AI agents end-to-end: map workflows, write prompts and conversation flows, integrate with customer APIs, create test sets, monitor live conversations, debug production issues, and iterate on agent quality with product feedback.
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The Lead Quality Engineer will set quality standards, mentor a QA team, improve testing strategies, and enhance automation in AI-driven workflows.
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Build full-stack features for AI voice and chat products using TypeScript, Node.js, React, and Python. Integrate ASR/TTS and LLM improvements, optimize production systems for latency and cost, participate in on-call rotations, and collaborate with ML and product teams to scale enterprise AI conversations.
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Lead a Product Engineering squad (8–15 engineers), prioritize people development, hiring, process, and predictable delivery. Drive AI-native practices, technical credibility, customer-focused outcomes, testing/validation, and cross-functional partnerships while owning team budget and headcount.
