Senior AI Engineer

NeueHealth

. Lead the end-to-end delivery of complex AI products including agentic workflows, RAG systems, and services .

Posted 10/6/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the delivery of complex AI products, with a strong focus on healthcare applications, compliance, and operational workflows. Proficient in Python and cloud services, with a proven track record in AI model optimization and technical leadership.

Highest-signal resume keywords

AI Product DeliveryPython ProficiencyCloud Services ExperienceHealthcare Compliance KnowledgeTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Workflow DesignService and Data-Contract DesignCI/CDObservabilityDebuggingReliability EngineeringModel Fine-TuningRAG SystemsAdversarial TestingProduction Telemetry

Soft Skills

CollaborationMentoringSelf-Directed Exploration

Tools & Technologies

AzureAWSGCPDatabricksKubernetesOpenTelemetryAzure AI FoundryAzure MLAgent BricksAI Observability Tools

Industry Keywords

PHI/PIIHealthcare AIClinical WorkflowsOperational WorkflowsCompliance ControlsValue-Based CareSafety ReviewGovernanceRegulated EnvironmentsEmerging AI Capabilities

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaKubernetesPythonScalaTypeScript

About the role

Key responsibilities & impact

Lead the end-to-end delivery of complex AI products including agentic workflows, RAG systems, and services
Collaborate with Product, Engineering, Data, and clinical and operational teams
Translate stakeholder needs into validated, access-aware AI workflows with clear system behavior, acceptance criteria, risk controls, and delivery trade-offs
Design AI workflow and RAG product lines, including ingestion, retrieval quality, attribution, confidence handling, agent tools, and human-review paths
Implement workflows with reliable AI control layers and optimize healthcare AI models across prompting, retrieval, reranking, fine-tuning, and model-selection approaches
Own healthcare AI evaluation and release frameworks, including adversarial testing, regression thresholds, release gates, and production telemetry
Provide senior technical leadership through design and code reviews, incident response, mentoring, and reusable engineering improvements
Deliver healthcare AI services using approved cloud capabilities and HITRUST-aligned controls for PHI/PII, security, privacy, auditability, responsible AI, and compliance

Requirements

What you’ll need

Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Science, Linguistics, or a related field; equivalent practical experience may be considered
Typically, 5+ years of relevant engineering experience, including ownership of complex production components or technical leadership of feature delivery
Hands-on experience delivering and operating production or near-production AI/ML/LLM-enabled applications
Strong software engineering expertise in service and data-contract design, testing, CI/CD, observability, debugging, reliability, and operational support
Strong proficiency in Python, Java, Scala, C#, TypeScript or a comparable modern language
Deep working knowledge of structured outputs, RAG, tool use, evaluations, guardrails, monitoring, and human-in-the-loop design
Experience with cloud services and data-intensive systems; ability to collaborate across structured-data products and unstructured-data pipelines
Demonstrated self-directed exploration of emerging AI capabilities through independently built prototypes, tools, experiments, or applications
Experience translating AI experimentation into production solutions for enterprise or regulated environments, with attention to safety, reliability, security, governance, and measurable outcomes
Preferred: Healthcare experience involving PHI/PII, clinical or operational workflows, payer/provider operations, auditability, safety review, compliance controls, or value-based care
Preferred: Experience with cloud AI and data platforms such as Azure, AWS, GCP, Databricks, Agent Bricks, Genie, Azure AI Foundry/Azure OpenAI, Azure ML, AKS/Kubernetes, OpenTelemetry, or AI observability and evaluation tooling
Preferred: Model benchmarking, selection, adaptation, fine-tuning, reranking, or other domain-model optimization techniques
Preferred: Experience leading technical initiatives across teams or mentoring several engineers

Benefits

Comp & perks

Work-from-home position
Equal Opportunity Employer committed to a diverse employee group