Principal Applied AI Engineer

Vi • Remote (EST/PST/CT),

10h

About The Position

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.

Requirements

• 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 Haves

• 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

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed