About the role

What will you do at AFL?

AFL manufactures industry-leading fiber optic cable, connectivity and

accessories and provides engineering and installation services for some of the

largest telecom customers in the world. Our company was founded in 1984 with a

single fiber optic cable and today, we manufacture thousands of products,

generate an excess of $4B in revenue, and employ approximately 11,000 associates

worldwide. At AFL, we recognize that our employees are our greatest asset. We

hire and train each individual, investing in them to ensure success in their

careers. With a commitment to professional development and growth, let us

connect you to your next career opportunity.

What We Offer:

* 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!

We are seeking a Lead AI Engineer to join our Business Operations team. This

position may be able to work remotely from anywhere within the United States.

The Lead AI Engineer is the first engineering hire on AFL's AI Enablement team,

responsible for designing, building, and deploying agentic AI systems that

automate the operational backbone of the business through workflow

orchestration, model adaptation, and analytics. Working directly with the AI

Enablement Manager, the Lead AI Engineer will help lay the technical foundation

the rest of the team will build on — including model selection and management,

deployment posture, orchestration patterns, evaluation and audit. As the team

grows, an AI Product Manager and AI Operations Specialists will join to take on

intake, sequencing, stakeholder coordination, and product ownership of deployed

solutions, allowing engineers to stay focused on build work.

Responsibilities

Key responsibilities/essential functions include:
Architecture & Technical Foundation
* Establishes the architectural patterns, evaluation practices, and deployment
standards for the team
* Makes framework and model recommendations that set the foundation for how the
team builds — evaluates orchestration frameworks, selects deployment
patterns, trains and fine-tunes models, and determines where managed
platforms end and custom build begins
Solution Design & Delivery
* Translates proposed business solutions into technical plans — defines product
life cycles, prioritizes the backlog, and breaks initiatives into buildable
work
* Owns solutions end-to-end: technical planning, architecture, build, deploy,
and the monitoring that keeps them honest in production
Production Reliability
* Builds the monitoring, evaluation, and regression detection systems that keep
production agents reliable — including logging, performance benchmarking, and
feedback loops that surface drift early
Governance & Collaboration
* Partners with data governance to ensure solutions meet compliance, data
quality, and operational standards
Personal Qualities:
* Innovative and tech-savvy, with deep curiosity about emerging AI capabilities
and how to apply them
* Analytical and detail-oriented, with a strong engineering mindset
* Collaborative and communicative, able to translate complex technical concepts
for non-technical stakeholders
* Self-directed and accountable, able to set technical direction and drive
execution independently

Qualifications

* Bachelor's degree in Computer Science or related field, or equivalent
experience
* 7+ years of software engineering experience with a strong full-stack
foundation — backend services, API design, system integration, and data
infrastructure
* Recent hands-on experience building AI or LLM-backed systems and shipping
them to 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
Working Conditions:
* Environment: Remote work environment (US-based).
* Travel: Occasional travel (domestic) as needed.

Which skills does this role require?

PythonAI developmentLLM-backed systemsSoftware engineeringSystem integrationData infrastructureAPI designModel selectionFine-tuningPrompt engineeringEvaluation frameworksCloud platformsArchitectureObservabilityMentoringTechnical leadershipAI EngineerBusiness OperationsFiber opticAgentic AIWorkflow orchestrationModel adaptationAnalyticsLLMFull-stackRegression detectionData governanceComplianceTechnical architecturePerformance benchmarkingBacklog managementStakeholder coordinationREST APIsLLMs

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