AI Engineer

Nsight Health

. Own the technical operation and continuous improvement of Nsight Health's AI phone agents for inbound and outbound patient calls .

Posted 10/14/2026full-timeRemote • United StatesMid-LevelSenior💰 $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI and ML engineering with a focus on NLP/NLU, ensuring HIPAA compliance and quality in healthcare applications. Proficient in building and managing AI-driven systems, including voice interaction technologies and data processing pipelines.

Highest-signal resume keywords

ML Engineering ExperienceNLP/NLU ExpertiseProduction Voice AI ExperiencePHI-Safe AI Pipeline DesignHealthcare Data Fluency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNatural Language ProcessingSpeech-to-TextConversational AIPrompt EngineeringData MinimizationMulti-Agent System DesignAcceptance Criteria DefinitionQuality AssuranceAI Pipeline Architecture

Soft Skills

Technical LiaisonCommunicationCollaborationProblem-SolvingInfluencing

Tools & Technologies

Anthropic Claude APIAWS BedrockOpenAI APIPostgreSQLJira APISlack WebhooksPagerDutyFive9TwilioLangChain

Industry Keywords

HIPAA ComplianceEHR Data ModelsClaims DataRemote Patient MonitoringClinical Context

Tech Stack

Tools & technologies

AirflowApacheAWSKafkaPostgresSparkSQL

About the role

Key responsibilities & impact

Own the technical operation and continuous improvement of Nsight Health's AI phone agents for inbound and outbound patient calls
Serve as technical liaison between Nsight Health and the IVA provider
Translate clinical and operational requirements into provider direction and communicate provider capabilities internally
Manage provider performance against quality and HIPAA compliance standards
Define acceptance criteria and build layered test harnesses for provider releases
Configure and tune AI phone agents to meet clinical and operational goals
Influence the provider's NLU engine design, tuning, accuracy, and continuous iteration
Build and own alerting by scraping provider data, classifying failure patterns, and firing automated alerts
Architect AI-driven quality intelligence pipelines that proactively surface failures and route them to owners
Build PHI-safe audio processing pipelines using local speech-to-text and in-memory PHI redaction
Maintain HIPAA-compliant data handling across AI pipelines and BAA-covered third-party integrations
Build AI-native tooling such as semantic search, vectorized data processing, and automated alerting
Report to the VP of Engineering and work closely with the EVP of Patient Experience and R&D team
Improve voice interaction outcomes for thousands of Medicare patients across 350+ clinics

Requirements

What you’ll need

4+ years of ML or AI engineering experience
At least 2 years working directly with production LLM integrations in systems serving real users
Deep NLP/NLU expertise, including intent recognition, entity extraction, and utterance design
Production voice AI experience with speech-to-text, TTS, or conversational AI with NLU
Production NLU training and tuning experience, including training data pipelines, utterance sets, accuracy measurement, and iteration
Healthcare data fluency, including claims data, RPM vitals streams, EHR data models, and AI on HIPAA-covered patient data
Hands-on multi-agent system design experience
Prompt engineering for classification and structured output at production volume
PHI-safe AI pipeline design, including in-memory redaction, local inference, and data minimization
Fluency with Anthropic Claude API, AWS Bedrock, and OpenAI API
Experience with vector and embedding infrastructure such as pgvector or Pinecone
Experience with agent and orchestration frameworks such as LangChain, LlamaIndex, or CrewAI
PostgreSQL and SQL fluency
Experience with alerting and issue-routing tools such as Jira API, Slack webhooks, or PagerDuty
Telephony platform familiarity, such as Five9 or Twilio
Daily demonstrated use of Claude Code, GitHub Copilot, or equivalent AI-assisted development tools; hard requirement
Bachelor's degree in Computer Science, Engineering, or a related field is preferred; relevant experience weighted heavily over educational credentials
Preferred: Whisper, Deepgram, AWS Transcribe, or TTS providers
Preferred: clinical or regulated audio context experience
Preferred: Tray.io workflow automation and integration experience
Preferred: AWS Glue and Apache ecosystem experience, including Airflow, Kafka, or Spark

Benefits

Comp & perks

Eligible for an annual performance-based bonus based on company and individual performance
PTO accrual based
Medical insurance options
Dental insurance options
Vision insurance options
Supplemental insurance options
401(k) plan with 3.5% company match
Company-provided equipment