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Lead AI Engineer - Agentic AI & Platform Development

Humana

Louisville, KY, US$129k – $178konsite

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About this role

Become a part of our caring community   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 buildin

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