Senior AI Delivery Lead - Production AI Systems

EBSCO Information Services, Inc.; Honolulu (HI); Remote; USD 197,000 - 282,000; Full time

Job summary

EBSCO Information Services, Inc. is standing up an AI delivery capability within its Data & AI organization.

We seek a Delivery Lead to guide a forward-deployed engineering pod, set technical direction for agentic AI systems, and partner across Product, Security, Customer Service, and Operations to accelerate AI value. You will own delivery outcomes, establish an intake–build–handoff model, and create reusable patterns and guardrails to scale AI across the enterprise.

Qualifications

• 10+ years in software, product, or AI delivery, including leadership of AI-powered production software
• Experience shipping production AI/ML systems end-to-end
• Hands-on fluency with LLM orchestration, RAG, and human-in-the-loop design

Responsibilities

• Lead the Forward-Deployed Engineering pod and own outcomes, roadmap, and team performance
• Manage the intake → build → hand-off delivery model with value/feasibility/data-risk scoring
• Set technical direction for production agentic systems (orchestration, long-running workflows, guardrails)
• Stand up delivery foundations: evaluation harness, guardrails, observability, reusable patterns
• Own cost-to-serve: model selection, prompt caching, token economics
• Partner with business sponsors to translate use cases into shipped systems
• Collaborate with vendors while protecting IP ownership
• Instrument and report impact on Speed/Quality/Cost/Learning metrics
• Scale the capability by seeding an embedded champion network

Skills

AI delivery

Team leadership

Cloud native (AWS)

LLM orchestration

RAG / vector search

Responsible AI

Tools

AWS

LLM tooling

MCP

Job description

EBSCO Information Services, Inc. is standing up an AI delivery capability within its Data & AI organization.

We seek a Delivery Lead to guide a forward-deployed engineering pod, set technical direction for agentic AI systems, and partner across Product, Security, Customer Service, and Operations to accelerate AI value. You will own delivery outcomes, establish an intake–build–handoff model, and create reusable patterns and guardrails to scale AI across the enterprise.