Senior AI Engineer

Humana

. Design, develop, and deploy full-stack AI-powered applications, including frontend experiences, APIs, backend services, and data pipelines .

Posted 11/3/2026full-timeUnited StatesSenior💰 $117,600 - $161,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying full-stack AI-powered applications, with a strong focus on integrating LLMs, developing backend services, and ensuring compliance in regulated environments. Proficient in optimizing AI systems for performance and reliability while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Full-Stack AI Application DevelopmentLLM Integration and Workflow OptimizationKubernetes and Docker DeploymentEvaluation Framework DesignRegulated Industry Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptJavaScriptAPIsDistributed SystemsData PipelinesEvaluation FrameworksPrompt StrategiesDocument ProcessingModel Performance Monitoring

Soft Skills

Problem-SolvingCommunicationCollaborationOwnershipIndependence

Tools & Technologies

OpenAIGoogle AIAzure AIAWS BedrockKubernetesDockerCI/CD PipelinesOCRVector DatabasesSemantic Search

Industry Keywords

HealthcareFinancial ServicesGovernmentPrivacyComplianceData ProtectionAuditabilityRegulated EnvironmentQuality MetricsHuman-in-the-Loop

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerJavaScriptKubernetesNext.jsPythonReactTypeScript

About the role

Key responsibilities & impact

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 prompt strategies, structured output frameworks, tool-calling capabilities, and fallback mechanisms
Design and implement RAG systems using embeddings, vector databases, and semantic search technologies
Build evaluation frameworks with benchmark datasets, regression testing, quality metrics, and human review workflows
Develop human-in-the-loop processes for clinicians and domain experts to validate AI outputs and provide feedback
Build and maintain document-processing pipelines, including OCR, document ingestion, metadata extraction, indexing, and search
Optimize AI systems for accuracy, latency, reliability, scalability, and cost efficiency
Implement observability, monitoring, logging, alerting, and incident response processes
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 business requirements into scalable solutions
Ensure solutions meet privacy, security, compliance, and auditability requirements in a regulated healthcare environment
Own AI solutions end-to-end from user experience and APIs through model orchestration, evaluation, infrastructure, and production operations

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or another quantitative or related technical discipline, or an equivalent combination of education and 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, 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
Must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets
Experience designing evaluation frameworks, testing strategies, prompt versioning, tracing, and model performance monitoring
Experience with agentic architecture, Model Context Protocol (MCP), tool orchestration frameworks, or autonomous workflows
Experience with React, Next.js, modern frontend development, and full-stack application architecture
Experience deploying and operating workloads in Kubernetes, Docker, and cloud environments
Experience with modern CI/CD practices and infrastructure automation
Experience working in regulated industries such as healthcare, financial services, or government
Familiarity with privacy, compliance, governance, and data protection requirements
Experience using AI-assisted development tools to improve engineering productivity and software quality
Strong problem-solving, communication, and collaboration skills
Responsible handling of sensitive and protected data in a highly regulated environment

Benefits

Comp & perks

Bonus incentive plan based on company and/or individual performance
Medical benefits
Dental benefits
Vision benefits
401(k) retirement savings plan
Paid time off
Company and personal holidays
Paid parental and caregiver leave
Short-term disability
Long-term disability
Life insurance