Senior Applied AI Engineer
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Job Description
Applied AI Engineer deploying real-time voice and document AI agents for health systems, providers, and pharma organizations. Owning integrations, production launches, and post-launch reliability.
Responsibilities:
- Own client engagements end to end, from discovery through production and the first months of operation
- Work with client operations, clinical, and IT teams to understand existing workflows
- Design, build, and deploy AI agents for healthcare and pharmaceutical operations
- Integrate agents with client systems including CRM, EHR/EMR, practice management, claims, and specialty pharmacy systems
- Build real-time voice capabilities involving telephony, streaming audio, speech input/output, and latency management
- Extract reliable structured data from unstructured healthcare documents
- Implement and monitor write paths into systems of record, including handling failed actions
- Establish post-launch testing, measurement, monitoring, and quality processes
- Develop reusable patterns and components for future deployments
- Feed field learnings back to Product and Platform Engineering
- Operate systems handling real patients under HIPAA
Requirements:
- Experience integrating LLMs into real workflows handling actual inputs and downstream handoffs
- Production experience with real-time systems such as WebSockets, streaming media, event-driven architectures, or high-throughput API services
- Experience integrating with external systems including CRM, EHR/EMR, claims, specialty pharmacy, or similar, including write operations
- Experience owning a whole system end to end
- Client-facing engineering experience with technical and non-technical stakeholders
- Strong Python plus TypeScript or Node
- Experience shipping production applications
- Ability to deploy and operate applications at scale on AWS or GCP
- Experience with containers, CI/CD, monitoring, and security practices
- Understanding of HIPAA-regulated environments and data-protection requirements
- Nice to have: voice or telephony infrastructure at scale, including Twilio, LiveKit, Pipecat, or Amazon Connect
- Nice to have: document AI and extraction from low-quality scanned input
- Nice to have: healthcare or pharma domain knowledge
- Nice to have: workflow engines, rules engines, or state machine architectures
- Nice to have: forward-deployed or professional services experience at an AI or data company
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