Senior AI Engineer - Voice & Agentic Systems

We're partnering with a well-funded, early-stage AI startup that is rebuilding how healthcare support is delivered using autonomous AI agents.

Backed by top-tier Silicon Valley investors and founded by experienced leaders from some of the world's most respected technology companies, the team is building an AI-native platform that combines human expertise with intelligent agents to automate complex healthcare workflows.

This isn't another chatbot company.

They're creating AI systems that coordinate real-world tasks, communicate with people over voice, learn continuously from production interactions, and become more capable with every conversation. The ambition is to build an AI platform that can manage increasingly complex workflows while allowing human specialists to focus where they create the most value.

The company is still small, giving engineers genuine ownership over architecture, product direction, and the core AI systems that will define the business.

We're looking for a Founding AI Engineer to build the intelligence layer that powers every AI agent across the platform.

Rather than focusing on one isolated model, you'll own the complete learning loop:

• Building production AI agents
• Designing evaluation frameworks
• Creating feedback pipelines from real user interactions
• Developing reinforcement learning and continuous improvement systems
• Shipping production AI that improves through usage

You’ll work directly alongside the founders, helping shape both the technical roadmap and the long-term AI strategy.

• Production AI agents handling complex real-world workflows
• Voice AI systems and conversational agents
• Agent orchestration and multi‑agent architectures
• Evaluation frameworks and automated benchmarking
• Reinforcement learning and feedback‑driven improvement pipelines
• Retrieval systems, memory, and long‑context reasoning
• Production monitoring, reliability, and quality measurement
• End‑to‑end AI infrastructure that scales from early customers to enterprise volumes

Engineers who have built and shipped real AI products rather than prototypes.

Strong backgrounds include:

• LLM applications and AI agents
• Evaluation frameworks
• RLHF, reward modeling, or feedback learning systems
• Agent orchestration
• Production AI infrastructure
• RAG and retrieval systems
• Voice AI