Principal Applied AI Engineer

 Posted 3 hours ago
     
5-10 years experience
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AI Summary

Build and deploy end-to-end AI-powered voice and messaging agents for healthcare and life sciences clients. Translate complex client workflows into technical agent designs and integrate them with EHR/EMR and CRM systems while ensuring HIPAA compliance.

We’re looking for a lead engineer who can take Vi’s AI agent capabilities and make them work in production healthcare environments. You’ll build and ship AI systems for clients — owning everything from data ingestion and CRM integration to real-time agent infrastructure and HIPAA-compliant delivery. This is a client-facing role: you work closely with enterprise customers to understand their workflows, then you build AI orchestrated workflows that automate them.

You’re comfortable with databases, data pipelines, AI/ML tooling, agent configuration, and the messy realities of integrating with healthcare data systems. You ship fast, you think in products, and you don’t wait for specs.

Key Responsibilities

  • Build and deploy AI-powered voice and messaging agents for healthcare and life sciences clients, end-to-end.
  • Translate client workflows into real agent workflow design. Run technical sessions with clients' clinical, IT, and ops teams; converting needs into prompts, tools, retrieval shapes, and vector stores.
  • Integrate with client data systems including CRMs, EHR/EMR platforms, specialty pharmacy systems, claims and Rx data feeds and build the ingestion pipelines to support them.
  • Write the production stack in TypeScript - agent runtime, routing, orchestration, evals; help build out the ML side in Python (training, embeddings, model registry); compose declarative guardrails & integrations within workflows. 
  • Engineer within HIPAA constraints: real-time API access to PHI (never stored at rest), de-identification pipelines, US-only data residency, encrypted recordings.
  • Design and maintain databases (relational and caching layers) that support both real-time agent operations and compliance audit trails.
  • Implement output guardrails ensuring agents remain informational and compliant with healthcare regulatory requirements.
  • Codify per-client configuration patterns into reusable components so each new client onboards faster than the last.
  • Collaborate with product, account management, and platform engineering to translate field learnings into platform improvements.

What We’re Looking For

  • 7+ years in a production engineering role shipping customer-facing software. Solutions engineering or consulting backgrounds qualify if you were writing and deploying production code, not just scoping it.
  • Fluency in modern programming languages (Javascript/Node, Typescript, Python, etc)
  • Experience building and operating real-time systems: WebSockets, streaming media, event-driven architectures, or high-throughput API services.
  • Production integration work with CRM platforms (Salesforce, HubSpot, or similar), healthcare data systems (EHR/EMR, claims, pharmacy), or data warehouse/lake connectors (Snowflake, Databricks, S3).
  • Have built retrieval and ingestion paths that feed agents reliable context with correct guardrails & caching in place.
  • Working knowledge of data engineering patterns: ETL/ELT pipelines, data quality checks, ingestion from heterogeneous sources.
  • Comfort with cloud infrastructure (AWS, GCP): containers, CI/CD, monitoring, and basic security practices.
  • Ability to work within HIPAA-regulated environments. You don’t need to be a compliance expert, but you understand why certain data can’t be logged and how to build systems that enforce it.
  • Strong client-facing communication: you can run a technical working session with a customer’s IT team and translate what you learn into engineering decisions.
  • Startup disposition: you build, you ship, you fix what breaks. Low ego, high agency.

Nice to Have

  • Voice or telephony infrastructure experience:  building or operating real-time call systems at scale.
  • LLM orchestration and agentic system design: prompt engineering, function calling, structured output, guardrails.
  • Healthcare or life sciences domain knowledge: patient services, specialty pharmacy, clinical operations, health plan operations.
  • Experience with workflow engines, rules engines, or state machine architectures.
  • Product sensibility: you think about user experience, not just system architecture. You’ve influenced product direction through technical insight.
  • Prior work at healthcare technology companies or AI-native startups building customer-facing agent systems.



Responsibilities

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Requirements

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Advantages

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Why choose Vi?

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Why choose Muuv?

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