Senior Applied AI Engineer

. Own client engagements end to end, from discovery through production and the first months of operation .

Posted 9/25/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in integrating AI agents within healthcare operations, ensuring compliance with HIPAA regulations while managing end-to-end client engagements. Proficient in deploying scalable applications on AWS or GCP, with a strong foundation in Python and TypeScript or Node.

Highest-signal resume keywords

AI Agent IntegrationReal-Time Systems ExperienceEnd-to-End System OwnershipClient-Facing EngineeringHIPAA Compliance Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptNodeReal-Time SystemsAPI ServicesData ExtractionApplication DeploymentMonitoring PracticesCI/CDContainers

Soft Skills

Client EngagementCollaboration with Stakeholders

Tools & Technologies

AWSGCPCRM SystemsEHR/EMR SystemsTelephony InfrastructureTwilioLiveKitPipecatAmazon Connect

Industry Keywords

HealthcarePharmaceuticalHIPAADocument AIWorkflow Engines

Tech Stack

Tools & technologies

AWSGoogle Cloud PlatformNode.jsPythonTypeScript

About the role

Key responsibilities & impact

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

What you’ll need

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