Job description

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key 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. Use your skills to make an impact Required Qualifications Bachelor s degree in Computer Science, Engineering, or a related technical 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. Preferred Qualifications Experience building AI systems where LLMs are part of the critical production workflow. 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. Success in This Role Successful candidates are energized by ambiguity, motivated by ownership, and excited to solve difficult problems where correctness matters. You enjoy building systems that are accurate, traceable, and trustworthy, and you view model failures as engineering challenges to be solved rather than limitations to be accepted. This role is best suited for engineers who want to own meaningful problems end-to-end and see their work directly impact on users and business outcomes. Technology Stack TypeScript React / Next.js Python PostgreSQL Gemini on Vertex AI OCR and Document AI technologies Docker Kubernetes Modern CI/CD platforms and tooling Additional Information This role operates in a highly regulated environment. Responsible handling of sensitive and protected data is a fundamental requirement and an essential part of our engineering culture. Work Style: This position follows a hybrid work schedule, requiring employees to work three days per week in the office and the remaining days remotely. Qualified candidates must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets. #enterpriseAI Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $141,100 - $194,000 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, “Humana”) offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About Us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com. Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

Requirements

Must-haves

Become a part of our caring community
Most AI engineering jobs are a thin wrapper around a model API. This role is different.
Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role.
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.

Nice-to-haves

Experience building AI systems where LLMs are part of the critical production workflow.
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.
Success in This Role
This role is best suited for engineers who want to own meaningful problems end-to-end and see their work directly impact on users and business outcomes.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapillmkubernetesdockerci/cdazureawspythontypescriptjavascriptreactnext.js

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Wellness