Lead AI Engineer

Humana; Dallas (TX); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Humana in Dallas seeks a Lead AI Applied Engineer to own the architecture and build critical AI-enabled products within a highly regulated healthcare landscape, transforming clinical documents and delivering trusted data.

You will lead LLM pipelines, define architectural direction, and ensure reliability, privacy, and auditability while remaining hands-on in design, coding, and production operations.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of software engineering experience, including production systems at scale.
• Proven track record delivering AI-enabled products or platforms to production.
• Hands-on experience integrating and operating LLMs in business workflows.
• Experience designing systems with structured outputs, RAG, agentic workflows, and evaluation pipelines.
• Strong architectural decision-making for AI-centric products.
• Leadership across engineering teams, architecture reviews, mentoring, and delivery execution.
• Strong programming in Python and/or TypeScript/JavaScript.
• Experience designing distributed systems, APIs, data platforms, and cloud-native apps.
• Reliability engineering, performance, and operational excellence.
• Balancing quality, latency, cost, security, and maintainability.

Responsibilities

• Own architecture, design, and evolution of full-stack AI applications including LLM pipelines.
• Design scalable AI solutions prioritizing reliability, accuracy, auditability, performance, and cost.
• Lead high-risk components with significant business impact.
• Define engineering standards for AI systems, including evaluation methodologies and observability.
• Lead design reviews and guide platform capability decisions.
• Evaluate technologies, models, and third-party solutions per requirements.
• Translate business goals into technical roadmaps and executable workstreams.
• Provide technical leadership across multiple projects with alignment to standards.
• Mentor engineers via reviews, pair programming, and guidance.
• Collaborate with product, clinical, and ops to meet regulatory needs.
• Own operations, deployment, monitoring, incident management, and reliability.
• Ensure privacy, security, governance in regulated healthcare environment.

Skills

Python

TypeScript/JavaScript

Distributed systems

Cloud-native

Reliability engineering

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes

Docker

React

Next.js

PostgreSQL

Vertex AI

Job description

Become a part of our caring communityYou have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself.

Become a part of our caring communityYou have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. 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 source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment.

Why Join Us

• Lead the architecture of production AI systems where LLMs are foundational to the product experience.
• Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies.
• Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness.
• Influence engineering culture and establish standards that shape how the team builds and ships AI products.
• Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population.
• Partner with highly skilled engineers while remaining deeply hands-on in coding, design, and production operations.
• Simplify complex solutions and drive pragmatic engineering decisions that maximize business value.

Key Responsibilities

• Own the architecture, design, and evolution of full-stack AI applications, including LLM pipelines, retrieval systems, agentic workflows, human-in-the-loop processes, and supporting platform services.
• Design and implement scalable AI solutions that prioritize reliability, accuracy, auditability, performance, and cost efficiency.
• Build and maintain the most complex and high-risk system components where architecture and implementation decisions have significant business impact.
• Define and enforce engineering standards for AI systems, including evaluation methodologies, structured outputs, observability, testing, fallback strategies, latency optimization, and cost controls.
• Lead technical design reviews and guide architecture decisions related to platform capabilities, AI systems, integrations, infrastructure, and software patterns.
• Evaluate and recommend technologies, frameworks, AI models, and third-party solutions based on technical and business requirements.
• Translate ambiguous business goals into clear technical strategies, roadmaps, and executable workstreams.
• Provide technical leadership across multiple projects, ensuring alignment with architectural standards and long-term platform objectives.
• Mentor and coach engineers through design reviews, code reviews, pair programming, and technical guidance.
• Partner with product, engineering, clinical, and operational stakeholders to deliver solutions that meet business and regulatory requirements.
• Own operational excellence, including deployment strategies, monitoring, incident management, and production reliability.
• Ensure all solutions comply with privacy, security, governance, and audit requirements within a regulated healthcare environment.

Required Qualifications

Use your skills to make an impact

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of software engineering experience, including experience designing and operating production systems at scale.
• Proven track record of delivering AI-enabled products or platforms into production environments.
• Deep hands-on experience integrating and operating LLMs within business-critical workflows.
• Experience designing systems that leverage structured outputs, tool calling, retrieval-augmented generation (RAG), agentic workflows, orchestration frameworks, and evaluation pipelines.
• Experience making architectural decisions for systems where AI is a core component of the product experience.
• Demonstrated success leading technical initiatives across engineering teams, including architecture reviews, technical planning, mentoring, and delivery execution.
• Strong programming skills in Python and/or TypeScript/JavaScript.
• Experience designing and operating distributed systems, APIs, data platforms, and cloud-native applications.
• Strong understanding of reliability engineering, system performance, scalability, and operational excellence.
• Ability to balance technical tradeoffs involving quality, latency, cost, security, and maintainability.

Preferred Qualifications

• Experience taking AI products from concept through production deployment and long-term operational ownership.
• Experience developing AI systems where LLMs are part of critical decision-support or operational workflows.
• Expertise in evaluation frameworks, benchmark datasets, regression testing, model quality measurement, and human review processes.
• Experience with agentic systems, Model Context Protocol (MCP), workflow orchestration, multi-step reasoning frameworks, and AI observability platforms.
• Experience with React, Next.js, modern frontend technologies, and full-stack application development.
• Experience deploying and managing workloads using Kubernetes, Docker, modern CI/CD platforms, and cloud-native technologies.
• Experience with Google Cloud Platform, Azure, AWS, Vertex AI, or comparable AI and cloud infrastructure platforms.
• Experience working in highly regulated industries such as healthcare, financial services, or government.
• Knowledge of privacy, compliance, security, and governance frameworks impacting AI and data-driven applications.
• Experience implementing AI-assisted development practices that improve engineering productivity and delivery speed.
• Excellent communication, collaboration, problem-solving, and leadership skills.

Leadership Expectations

• Lead through technical excellence, sound engineering judgment, and hands-on execution.
• Establish standards that drive consistency, reliability, and quality across the engineering organization.
• Influence architectural direction while balancing innovation with operational stability.
• Foster a culture of ownership, continuous learning, mentorship, and accountability.
• Drive alignment across teams and stakeholders to ensure successful delivery of strategic initiatives.

Success in This Role

Successful candidates are passionate about building production-grade AI systems where correctness, transparency, and reliability matter. You enjoy solving difficult engineering problems, making thoughtful architectural decisions, and helping teams deliver high-impact solutions. You are equally comfortable defining system architecture, mentoring engineers, reviewing designs, responding to production incidents, and writing code for the most critical parts of the platform.

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 a core part of our engineering culture. Success in this role requires a commitment to building secure, compliant, auditable, and trustworthy AI systems.

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.