Role: Software Engineer

Experience: ~2 years | Focus: Voice AI, Chat AI, and AI Evaluation & Training

Position Overview

We are seeking a hands-on AI Full Stack Developer (~2 years of experience) to help us build and improve our AI applications — Voice AI agents, Chat AI assistants, and the systems we use to evaluate and train them. You will work across the stack: designing and developing application features, integrating LLMs and speech (STT/TTS) services, building real-time conversational flows, and creating the evaluation harnesses and datasets that make our AI measurably better over time. This is a high-impact role for an early-career engineer who is excited about applied AI and wants to ship production conversational systems.

Roles & Responsibilities

Design, develop, unit test, and deploy full-stack features for Voice AI and Chat AI products.
Integrate and orchestrate LLMs (e.g., Claude / GPT-class models) into conversational flows, prompts, and tool-calling / function-calling pipelines.
Build and maintain Voice AI components — real-time audio streaming (WebSockets),



speech-to-text and text-to-speech integrations, and low-latency turn-taking.
Develop Chat AI features including RAG (retrieval-augmented generation), knowledge-base integration, and context/session management.
Build AI evaluation and training tooling: prompt/response test suites, automated and LLM-as-judge evaluations, golden datasets, regression checks, and quality dashboards.
Curate, label, and manage datasets used for fine-tuning, prompt optimization, and evaluation.
Write reusable, extensible, and well-tested code; participate actively in code reviews.
Collaborate across Dev, QA, DevOps, Architects, and Product to design and deliver solutions.
Work with L2 and customer support teams to investigate and resolve AI-related customer issues.
Participate in all scrum ceremonies and follow Agile development practices.
Troubleshoot AI applications in a large-scale enterprise setting, including

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