- Company Name
- Hippocratic AI
- Job Title
- AI Engineer
- Job Description
-
**Job Title:** AI Engineer
**Role Summary:** Design, build, and optimize production-grade AI pipelines for voice‑enabled generative healthcare agents, integrating large language models, retrieval‑augmented generation (RAG), and real‑time speech interfaces to deliver safe, scalable, and human‑centered AI experiences.
**Expectations:**
- Deliver end‑to‑end, robust, and maintainable AI systems that meet clinical safety standards.
- Translate complex healthcare workflows into deployable AI solutions.
- Continuously improve model performance, safety testing, and observability.
**Key Responsibilities:**
- Architect and implement scalable RAG and multi‑agent pipelines for voice‑based healthcare interactions.
- Prototype and launch zero‑to‑one features using state‑of‑the‑art LLMs, retrieval systems, and streaming architectures.
- Collaborate cross‑functionally with product managers, clinical experts, and researchers to align AI capabilities with user needs.
- Develop AI‑native workflows that support real‑time, conversational, and long‑running interactions across diverse healthcare contexts.
- Drive continuous improvement in model evaluation, safety testing, and system observability to ensure compliance with clinical safety standards.
**Required Skills:**
- 3+ years professional experience in software, ML, or AI engineering.
- Proven track record of building, deploying, and scaling AI/ML products in production environments.
- Strong Python proficiency, including distributed systems, RESTful APIs, and data pipeline development.
- Deep understanding of prompt engineering, vector databases, and retrieval‑augmented generation (RAG).
- Familiarity with voice agents, speech recognition, or swift learning in these domains.
- Experience with cloud platforms (AWS, GCP, Azure) and DevOps practices (Terraform, CI/CD, monitoring).
- Excellent communication and collaboration skills; ability to work quickly in high‑impact, cross‑functional teams.
**Nice‑to‑Have Skills:**
- Experience deploying LLM‑based or multi‑agent systems at scale.
- Hands‑on work with speech recognition, text‑to‑speech, or streaming architectures for real‑time AI experiences.
- Prior exposure to healthcare, safety‑critical domains, or regulated product development.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience).
- Certifications in cloud platforms or AI/ML (e.g., AWS Certified Machine Learning Specialist, GCP ML Engineer) are a plus but not mandatory.