Senior AI Engineer – Healthcare AI at Scale

Humana Inc

New York (NY)

Hybrid

USD 141,000 - 194,000

Full time

14 days+

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Benefits offered by this job

Medical, dental, and vision benefits
401(k) retirement savings plan
Paid time off
Disability insurance
Life insurance
Many other opportunities

Job summary

Humana, Inc. is seeking a Senior AI Applied Engineer to design, build, deploy, and operate production AI systems at scale within one of the country’s largest health insurers.

You will own end‑to‑end solutions from user experience and APIs to model orchestration and production operations. You will work on extraction, retrieval, and agentic workflows with strong emphasis on accuracy, explainability, and auditability in a regulated healthcare environment.

Qualifications

  • Bachelor's degree in CS/Engineering or related field or equivalent practical experience.
  • 5+ years of experience building and operating production software systems.
  • Experience developing backend services, APIs, distributed systems, or data-intensive applications.
  • Hands-on experience integrating LLMs into production applications beyond simple chat interfaces, including structured outputs, tool calling, retrieval‑augmented generation (RAG), agents, or multi‑step workflows.
  • Experience with at least one major AI platform or model provider such as OpenAI, Anthropic, Google, Azure AI, or AWS Bedrock.
  • Strong programming skills in Python and/or TypeScript/JavaScript.
  • Experience debugging, monitoring, and supporting production applications used by real customers.
  • Ability to work independently, navigate ambiguity, and take ownership of projects from concept through deployment.

Responsibilities

  • Design, develop, and deploy full-stack AI-powered applications, including frontend experiences, APIs, backend services, and data pipelines.
  • Build and optimize LLM-based workflows for information extraction, classification, retrieval, summarization, and agentic processes.
  • Develop robust prompt strategies, structured output frameworks, tool-calling capabilities, and fallback mechanisms to improve reliability.
  • Design and implement retrieval-augmented generation (RAG) systems using embeddings, vector databases, and semantic search technologies.
  • Build evaluation frameworks, including benchmark datasets, regression testing, quality metrics, and human review workflows.
  • Develop human‑in‑the‑loop processes that enable clinicians and domain experts to validate AI outputs and provide feedback for continuous improvement.
  • Build and maintain document‑processing pipelines, including OCR, document ingestion, metadata extraction, indexing, and search capabilities.
  • Optimize AI systems for accuracy, latency, reliability, scalability, and cost efficiency.
  • Implement observability, monitoring, logging, alerting, and incident response processes for production systems.
  • Deploy and operate services in cloud‑native environments using Kubernetes, Docker, CI/CD pipelines, and modern infrastructure tooling.
  • Collaborate with product, engineering, clinical, and operational stakeholders to translate complex business requirements into scalable solutions.
  • Ensure solutions meet privacy, security, compliance, and auditability requirements within a regulated healthcare environment.

Skills

Backend services
APIs
Distributed systems
Data-intensive apps
LLMs integration
Python
TypeScript/JavaScript
Debugging production apps
Independent worker
Ambiguity ownership

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

OpenAI
Azure AI
AWS
Kubernetes
Docker
CI/CD

Job description

Humana, Inc. is seeking a Senior AI Applied Engineer to design, build, deploy, and operate production AI systems at scale within one of the country’s largest health insurers.

You will own end‑to‑end solutions from user experience and APIs to model orchestration and production operations. You will work on extraction, retrieval, and agentic workflows with strong emphasis on accuracy, explainability, and auditability in a regulated healthcare environment.

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