Senior AI Systems Engineer for Production LLMs

Humana; Boston (MA); Hybrid; USD 118,000 - 162,000; Full time

Job summary

Humana is seeking a Senior AI Applied Engineer in Boston to design, build, deploy, and operate scalable AI systems that read medical records, extract structured facts, and route ambiguous cases to experts. You will own end-to-end solutions across UX, APIs, model orchestration, evaluation, and production operations.

The role emphasizes production-grade AI, observability, and compliance within a regulated healthcare environment, with hybrid office expectations and collaboration with clinical and

Qualifications

• Bachelor's degree in Computer Science, Engineering, Math, Statistics, or related field.
• 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 apps beyond basic chat interfaces, including structured outputs, tool calling, and RAG.

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 for reliability.
• Design and implement retrieval-augmented generation (RAG) systems using embeddings, vector databases, and semantic search.

Skills

Python

TypeScript/JavaScript

LLM integration

Distributed systems

API development

React/Next.js

Education

Bachelor's degree in Computer Science

Tools

Kubernetes

Docker

Job description

Humana is seeking a Senior AI Applied Engineer in Boston to design, build, deploy, and operate scalable AI systems that read medical records, extract structured facts, and route ambiguous cases to experts. You will own end-to-end solutions across UX, APIs, model orchestration, evaluation, and production operations.

The role emphasizes production-grade AI, observability, and compliance within a regulated healthcare environment, with hybrid office expectations and collaboration with clinical and