This role pays less than
58%
of similar roles. Most pay
$191,112–$285,000
— the shaded band above.
At the midpoint, this role pays about
$226k
versus about
$238k
for comparable roles.
Based on 240 similar postings.
Employer
About Pacific Life
Pacific Life is a life insurance company offering a wide range of life insurance, annuity, and investment products and services to individuals, businesses, and pension plans. Industry: Life Insurance & Annuities
Pacific Life currently has
26 open roles
on FindRole.
Listed pay typically runs
$145,080–$177,320
across 24 roles with salary data.
Sr Director AI Enterprise Engineering joins the Engineering Excellence team to advance engineering through agentic adoption and the operationalization of AI capabilities into secure, production-grade systems. This role oversees four key areas: Code & Delivery, Engineering in Test, Reliability & Telemetry, and Security & Compliance. The successful candidate will define the enterprise AI Engineering Build roadmap, manage the Build Register for platform tools, and lead the delivery of LLM integrations, RAG systems, and agentic workflows. Core responsibilities include establishing MLOps and LLMOps practices, ensuring Responsible AI compliance, and managing technical risk in a regulated industry environment. The role requires expertise in cloud-native architecture across Azure, AWS, or GCP, as well as proficiency in CI/CD, observability, and automated test generation to drive productivity, quality, and reliability across the enterprise engineering landscape.
Define and execute the enterprise AI Engineering Build roadmap aligned with business outcomes and platform adoption goals.
Manage the Build Register as the system of record for all AI engineering platforms, tools, and delivery commitments.
Lead the delivery of production-ready AI capabilities including LLM integration, RAG systems, and agentic workflows.
Establish production-grade MLOps and LLMOps practices covering CI/CD, model lifecycle governance, monitoring, and evaluation.
Ensure all AI engineering platforms meet enterprise standards for security, privacy, compliance, and Responsible AI.
Partner with CISO and risk leadership to manage high-risk releases and ensure secure-by-default engineering practices.
Build and scale a high-performing engineering organization through hiring, leadership development, and capability growth.
Drive cross-functional alignment across engineering, product, platform, and security teams to ensure coordinated execution.
What we're looking for
Minimum 20 years of engineering experience is required.
At least 8 years of experience leading teams at a Director or higher level is required.
Proven track record leading multi-team platform or AI engineering organizations at Director+ scope is required.
Deep expertise in at least two domains such as Developer Experience, Software Engineering in Test, SRE/Observability, or Application Security is required.
Hands-on experience building and scaling production AI/ML systems including LLMs, ML pipelines, or AI platforms is required.
Strong understanding of cloud-native architecture across Azure, AWS, or GCP is required.
Experience implementing MLOps, LLMOps, and AI lifecycle governance practices is required.
Experience in regulated industries (financial services, insurance, or healthcare) is preferred.
LLM
Vector Databases
Agentic Orchestration
MLOps
AWS
Azure
GCP
Docker
Kubernetes
PLM
CFD
FEA
Six Sigma
Data Engineering
Digital Thread
Model Based Systems Engineering