Lead AI Engineer, Business Operations

AFL

Lead AI Engineer responsible for architecting and delivering AI solutions at AFL. Collaborate with cross-functional teams to optimize business operations and improve automated processes.

Posted 7/24/2026full-timeDallas • Texas • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in software engineering and architecture, with a strong focus on AI and LLM-backed systems. Capable of leading teams, optimizing operational processes, and ensuring compliance and reliability in production environments.

Highest-signal resume keywords

Software Engineering ExperienceAI Development PracticesPython ProficiencyFull-Stack ArchitectureTeam Leadership

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software EngineeringArchitectureAPI DesignSystem IntegrationData InfrastructureAI Systems ArchitectureModel SelectionFine-TuningPrompt EngineeringTesting

Soft Skills

Strong Communication SkillsMentoring

Tools & Technologies

Cloud Platforms

Certifications & Qualifications

Bachelor's Degree in Computer Science

Industry Keywords

AI EnablementData GovernanceOperational StandardsMonitoring SystemsProduction Reliability

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

Establishes the architectural patterns, evaluation practices, and deployment standards for the team
Makes framework and model recommendations that set the foundation for the team
Collaborates with the AI Enablement Manager and business unit to optimize operational processes, owning the infrastructure architecture and translating strategic direction into technical plans, product life cycles, a prioritized backlog, and buildable work
Owns solutions end-to-end: technically planning, architecture, build, and deployment, then continuously monitors, iterates, and improves them to keep them reliable in production
Partners with data governance to ensure solutions meet compliance, data quality, and operational standards
Builds and continuously maintains the monitoring, evaluation, and regression detection systems that keep production agents reliable over time, including logging, performance benchmarking, and feedback loops that surface drift early.
Leads the team as it grows, onboarding new team members like AI Product Manager and AI Operations Specialists for intake, sequencing, stakeholder coordination, and product ownership of deployed solutions.

Requirements

What you’ll need

Bachelor's degree in Computer Science or related field, or equivalent experience
5+ years of software engineering and architecture experience with a strong full-stack foundation — backend services, API design, system integration, and data infrastructure
Recent hands-on experience architecting and delivering AI or LLM-backed systems in production
Experience architecting solutions from scratch and owning them through deployment, observability, testing, and ongoing reliability
Experience with AI development practices — model selection, fine-tuning, prompt engineering, evaluation frameworks, and understanding when each approach is the right fit
Proficiency in Python; experience with cloud platforms
Experience mentoring engineers and setting technical direction across multiple initiatives
Strong communication skills with both technical and non-technical stakeholders.

Benefits

Comp & perks

Flexible time off policy
401K Company match (up to 4% — dollar for dollar)
Professional development, training, and tuition reimbursement programs
Excellent medical, dental, vision, and life insurance policy options
Opportunities for career advancement with an industry leading company!