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You 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.
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.
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.
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
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.
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.
$170,800 - $234,800 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.
