Humana is seeking a Lead AI Engineer to provide technical leadership in the design, development, and scaling of production-grade Agentic AI solutions that accelerate AI for Software Development Lifecycle (SDLC) initiatives across the enterprise.
This role will lead the development of intelligent agents, agent orchestration frameworks, AI runtimes, developer tooling, and platform services that enable engineering teams to safely and effectively leverage AI at enterprise scale. The ideal candidate combines deep technical expertise with strong leadership capabilities and thrives in a hands-on environment where innovation, execution, and operational excellence are equally valued.
As a Lead AI Engineer, you will help define how AI capabilities are built, governed, deployed, and scaled across the organization while delivering measurable business outcomes through modern AI platforms and engineering solutions.
Key Responsibilities
Design and Build Production-Grade Agentic AI Solutions
- Lead the architecture, engineering, deployment, and scaling of enterprise AI solutions that support software delivery modernization initiatives.
- Design and develop intelligent AI agents that enhance software development, testing, security, operations, and developer productivity workflows.
- Build agent orchestration capabilities that enable multiple agents to collaborate across SDLC processes and workflows.
- Develop AI-powered services for code generation, code review, testing automation, documentation generation, incident response, and developer assistance.
- Create reusable APIs, SDKs, frameworks, and accelerators that simplify AI adoption across engineering teams.
- Integrate AI solutions with enterprise engineering platforms, including GitHub, Azure DevOps, ServiceNow, Jira, SonarQube, Snyk, and internal developer platforms.
- Ensure AI systems are secure, reliable, scalable, observable, and compliant with enterprise standards.
Provide Technical Leadership and Engineering Excellence
- Lead technical design sessions, architecture reviews, and implementation activities for AI platform and Agentic AI initiatives.
- Establish engineering standards, best practices, and design patterns for AI development, platform engineering, testing, automation, and software quality.
- Mentor engineers through code reviews, design reviews, pair programming, coaching, and technical guidance.
- Drive modern engineering practices, including CI/CD, Infrastructure as Code (IaC), observability, resiliency, operational readiness, and DevSecOps.
- Partner with Enterprise Architecture, Security, Product Management, and Platform Engineering teams to ensure alignment with enterprise standards and strategic objectives.
- Contribute to technical roadmaps, delivery planning, engineering maturity initiatives, and organizational capability development.
Drive Innovation and Emerging Technology Adoption
- Research and evaluate emerging AI technologies, orchestration frameworks, foundation models, tooling, and industry trends.
- Develop prototypes, proofs of concept, and pilot solutions that validate business value and technical feasibility.
- Explore advancements in agent orchestration, multi-agent systems, reasoning frameworks, developer productivity tools, and autonomous workflows.
- Collaborate with business, product, and architecture leaders to define future-state AI platform capabilities and technology strategies.
- Identify opportunities to improve engineering productivity, software quality, operational efficiency, and developer experiences through AI-driven solutions.
- Participate in AI communities of practice and contribute to enterprise technology enablement initiatives.
Build Scalable AI Platforms and Shared Services
- Design and develop scalable platform services that support enterprise-wide AI consumption and adoption.
- Create reusable agent frameworks, runtime services, governance controls, operational tooling, and developer enablement capabilities.
- Engineer highly available, resilient, secure, and cloud-native architectures capable of supporting large-scale AI workloads.
- Build capabilities for observability, auditing, governance, policy enforcement, FinOps, and responsible AI management.
- Establish reusable architecture patterns and implementation frameworks that accelerate onboarding and delivery of new AI use cases.
- Promote platform adoption through self-service capabilities, documentation, automation, and developer-friendly experiences.
- Partner with platform, infrastructure, and operations teams to ensure long-term scalability, reliability, and sustainability.
Champion Responsible AI Practices
- Ensure AI solutions adhere to enterprise standards for security, privacy, compliance, governance, and responsible AI.
- Define and implement evaluation frameworks that measure model performance, accuracy, reliability, safety, business impact, and operational effectiveness.
- Establish standards for AI observability, monitoring, tracing, auditing, explainability, and risk management.
- Design and implement guardrails for agent behavior, tool usage, human oversight, policy enforcement, and data protection.
- Collaborate with Enterprise Information Protection, Security, Compliance, Risk, Governance, and Architecture teams to enforce approved controls and standards.
- Drive adoption of responsible AI engineering practices including bias mitigation, transparency, explainability, continuous evaluation, and lifecycle governance.
- Ensure AI systems maintain auditability, traceability, accountability, and operational oversight at enterprise scale.
Use your skills to make an impact
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent professional experience.
- 8+ years of software engineering experience designing and building enterprise applications and platforms.
- 3+ years of experience building, deploying, or leading production AI/ML solutions.
- Strong expertise with Large Language Models (LLMs), retrieval-augmented generation (RAG), vector search technologies, prompt engineering, and AI orchestration frameworks.
- Experience designing and implementing AI-powered applications, services, or platforms in production environments.
- Proficiency in Python and at least one additional modern programming language, preferably C#/.NET.
- Experience developing cloud-native applications and services using Azure, AWS, or Google Cloud Platform.
- Strong knowledge of software architecture, distributed systems, APIs, microservices, testing strategies, CI/CD, DevSecOps, and platform engineering.
- Experience implementing observability, monitoring, resilience, and operational support practices for production systems.
- Demonstrated ability to lead complex technical initiatives and influence technical decisions across multiple teams and stakeholders.
- Strong communication, collaboration, mentoring, and problem-solving skills.
Preferred Qualifications
- Experience designing and deploying agentic or autonomous AI systems in production environments.
- Experience building reusable AI platforms, shared services, developer tooling, or enterprise AI capabilities.
- Experience with multi-agent orchestration frameworks, AI runtimes, workflow automation, and intelligent agent architectures.
- Familiarity with model evaluation frameworks, fine-tuning approaches, and advanced machine learning techniques.
- Experience delivering AI-powered developer productivity solutions or AI-assisted engineering platforms.
- Experience working within regulated or highly governed environments, including healthcare, financial services, or government sectors.
- Knowledge of AI governance, responsible AI practices, model monitoring, and risk management frameworks.
- Experience with GitHub, Azure DevOps, ServiceNow, Jira, SonarQube, Snyk, and modern software engineering toolchains.
- Contributions to open-source projects, patents, technical publications, conference presentations, or industry thought leadership.
Success in This Role
Successful candidates are passionate builders who enjoy solving complex technical challenges and transforming emerging AI capabilities into production-ready solutions.
You will thrive in this role if you:
- Enjoy building innovative products and platforms from concept through production.
- Can effectively move between strategic discussions, architecture design, and hands-on coding.
- Balance innovation with practicality and operational excellence.
- Enjoy mentoring engineers and helping teams achieve success.
- Focus on business outcomes as much as technical implementation.
- Challenge assumptions, simplify complexity, and deliver measurable value.
- Maintain a strong bias toward action while upholding engineering quality and governance standards.
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.
$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, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities.
