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About This Role
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Humana is seeking a Lead Full Stack Engineer, AI Solutions to lead the design, development, and deployment of scalable digital platforms and AI\-enabled solutions across enterprise environments. This role combines hands\-on full stack engineering leadership with forward\-deployed problem solving, partnering closely with business leaders, architects, and cross\-functional teams to translate complex, evolving requirements into secure, production\-grade systems.
The ideal candidate brings deep experience across front\-end and back\-end development, cloud\-native architecture, platform engineering, and modern AI/ML operations. This person will lead technical direction, mentor engineers, and work directly with stakeholders to build high\-quality solutions that improve business outcomes and align with enterprise standards, governance, and modernization initiatives.This position requires a physical presence in one of the following market locations: Louisville, KY, Dallas, TX, Washington, DC, Chicago, IL, Ft. Lauderdale, FL, or New York City, NY.
Key Responsibilities:
- Lead technical architecture, solution design, and engineering vision for business\-critical platforms and AI\-enabled applications
- Serve as a senior technical leader across all stages of software development, including front\-end development, back\-end development, database integrations, APIs, user experience, hosting, and server management
- Translate ambiguous business problems into scalable, production\-ready solutions by partnering with business leaders, solution owners, and enterprise technology teams
- Drive discovery and workflow mapping to identify automation opportunities, evaluate technical feasibility, and define success metrics
- Design and prototype cloud\-native and AI\-enabled solutions, including application architecture, system integrations, deployment patterns, and operational models
- Build and deploy production\-grade applications, RESTful APIs, AI/ML pipelines, and distributed services using approved enterprise technology patterns
- Lead by example through hands\-on engineering across platform, backend, frontend, and mobile technologies
- Mentor and coach a small team of high\-performing engineers, fostering technical excellence, accountability, and continuous improvement
- Review code, pull requests, and architecture decisions, providing constructive and actionable feedback
- Evaluate problems strategically and tactically, using strong problem\-solving skills, data structures, and algorithms to determine the best course of action
- Partner with senior business and functional leaders to define technical direction and support enterprise decision\-making
- Collaborate with architecture, review, and governance teams, including ARB/TRB and EA/EAI stakeholders, to align solutions with enterprise standards
- Support implementation of Cloud 3\.0 and modernization design patterns, including onboarding, development readiness, deployment, troubleshooting, and security alignment
- Ensure solutions comply with enterprise processes for architecture review, AI governance, cloud onboarding, and operational readiness
- Investigate and recommend new technologies, frameworks, tools, and engineering practices that improve speed, quality, scalability, and maintainability
- Optimize systems based on stakeholder and user feedback, and document workflows and implementation details for operational handoff and long\-term support
- Contribute insights from delivery experiences back to internal product, platform, and architecture teams to improve reusable enterprise capabilities
Use your skills to make an impact
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Required Qualifications
- Bachelor’s degree in Computer Science or a related field
- 8\+ years of progressive IT experience, including senior\-level software engineering experience on large\-scale technology initiatives
- 2\+ years of project or technical leadership experience
- Demonstrated ability to lead significant design and development efforts with minimal supervision
- Experience building scalable web platforms, enterprise applications, and highly available web services
- Strong full stack engineering experience across modern front\-end and back\-end technologies
- Tech lead\-level proficiency in one or more programming languages and frameworks such as TypeScript, Node.js, Java, Spring/Spring Boot, Vue.js, Angular, or similar
- Experience with React Native
- Experience with JSON, RESTful web services, client\-server interactions, and microservices patterns
- Experience designing solution architecture and delivering secure, scalable cloud\-native systems
- Knowledge of Azure Cloud Services or equivalent cloud platforms
- Experience with infrastructure and security as code
- Experience with containerization and orchestration technologies such as Docker, Kubernetes, and AKS
- Demonstrated experience with machine learning and artificial intelligence development operations, including implementing, maintaining, and monitoring ML/AI pipelines using industry\-standard tools and frameworks
- Strong understanding of Agentic AI concepts and processes
- Ability to work effectively with incomplete and evolving requirements, using sound judgment and technical insight to drive progress
- Strong communication and presentation skills with technical and non\-technical stakeholders
- Experience collaborating with governance and review bodies and cross\-functional teams in enterprise environments
- Experience working within Centers of Excellence (COEs) and executing established playbooks
- Strong time management skills and the ability to deliver high\-quality outcomes on schedule
- Comfortable giving and receiving feedback across engineering teams and broader organizational stakeholders
Preferred Qualifications
- Master’s degree in Computer Science, Engineering, or a related field
- Experience with Adobe Experience Platform
- Experience with Generative AI tools and AI platforms on GCP, Azure, or other cloud environments
- Background in forward\-deployed engineering, consulting\-style delivery, or embedded enterprise solution development
- Experience integrating AI solutions into real\-world business workflows while accounting for compliance, operational constraints, and enterprise standards
Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required.Scheduled Weekly Hours
40Pay 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.
$129,300 \- $177,800 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, volunteer time off, paid parental and caregiver leave), short\-term and long\-term disability, life insurance and many other opportunities.About us
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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.
Salary Context
This $129K-$177K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Humana, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($153K) sits 34% below the category median. Disclosed range: $129K to $177K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Humana AI Hiring
Humana has 7 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, AI Software Engineer, AI Product Manager. Positions span Remote, US, New York, NY, US, Fort Lauderdale, FL, US. Compensation range: $173K - $284K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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