Ambient Listening Engineer

Overview

DrFirst is seeking an Ambient Listening Engineer to join our Provider Solutions, eRx Retail team. You will build the technology that lets ambient AI quietly and reliably capture, transcribe, and structure spoken conversations, whether a provider-patient encounter or another clinical interaction, so information moves seamlessly to where it is needed. You will work at the intersection of real-time audio pipelines, speech and language models, and clinical workflow, with a bias toward shipping working software and iterating quickly alongside a small, tight-knit team. This role suits a developer who excels at hands-on implementation and thrives in a close-knit, collaborative environment.

Responsibilities

• Design, build, and maintain real-time and near-real-time ambient audio capture and streaming pipelines, from device and microphone input through transcription and downstream processing.
• Integrate and fine-tune speech-to-text (ASR), speaker diarization, and noise-suppression models to maximize accuracy in noisy, multi-speaker clinical environments.
• Build the services and APIs that turn raw ambient audio into structured, actionable output such as clinical notes, summaries, or discrete data elements for downstream systems.
• Partner closely with product, clinical informatics, and design to translate ambiguous workflow problems into working prototypes quickly.
• Own reliability, latency, and accuracy metrics for the ambient listening pipeline; instrument, monitor, and continuously improve them in production.
• Implement privacy- and security-conscious handling of audio and derived data, in line with HIPAA and other applicable regulatory requirements.
• Evaluate and integrate third-party and open-source speech and LLM models where they accelerate the roadmap, balancing build-vs-buy tradeoffs.
• Participate in code reviews, design discussions, and the on-call rotation for the services you own.

Qualifications

Required Qualifications

• 3+ years of professional software engineering experience, with a track record of shipping and operating production systems end to end.
• Hands-on experience with real-time or streaming audio and data pipelines (e.g., WebRTC, gRPC streaming, Kafka, or similar).
• Practical experience with speech-to-text, NLP, or applied machine learning models, whether integrating third-party APIs (e.g., Whisper, Deepgram, Azure Speech) or fine-tuning your own.
• Strong backend engineering skills in a language such as Python, Go, or Java, and comfort working across the stack when needed.
• A demonstrated preference for hands-on building over pure architecture or process; you would rather prototype and learn than spend weeks in design docs.
• Experience working in a small, fast-moving team where roles overlap and everyone pitches in outside a narrow job description.
• Familiarity with cloud infrastructure (AWS, Azure, or GCP) and containerized deployment (Docker, Kubernetes).
• Clear written and verbal communication, and comfort collaborating directly with clinical or non-technical stakeholders.

Preferred Qualifications

• Experience in healthcare technology, clinical documentation, or ambient/voice AI products specifically.
• Familiarity with HIPAA, SOC 2, or other healthcare and security compliance frameworks.
• Experience with LLM-based summarization or structured data extraction from unstructured text.
• Background in audio signal processing or acoustics.