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Pacific Life Insurance Company
Sr Director AI Enterprise Engineering
Career Insights for Artificial Intelligence Engineer (General)
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Based on California data
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$160,491 / year median in California
Job Description
Job Description:
Providing for loved ones, planning rewarding retirements, saving enough for whatever lies ahead- our policyholders count on us to be there when it matters most. It's a big ask, but it's one that we have the power to deliver when we work together. We collaborate and innovate
- pushing one another to transform not just Pacific Life, but the entire industry for the better. Why? Because it's the right thing to do. Pacific Life is more than a job, it's a career with purpose. It's a career where you have the support, balance, and resources to make a positive impact on the future
- including your own.
Scope Portfolio:
Enterprise AI engineering platforms including CI/CD, AI-assisted development, test generation and quality intelligence, observability/AIOps, and continuous security and complianceOperating Model:
Product based delivery with shared artifacts (Build Register) and continuous feedback loops (Spec Build Apply)Enterprise Impact:
Platforms consumed broadly across engineering to drive productivity, quality, and reliability Responsibilities Define and execute the enterprise AI Engineering Build roadmap, ensuring priorities are clearly aligned to business outcomes, platform adoption goals, and enterprise engineering needs.Build portfolio management:
Own the Build Register as the system of record for AI engineering platforms, tools, components, and delivery commitments.Planning and prioritization:
Operate Spec Build planning loops, using adoption signals and enterprise feedback to shape roadmap priorities.AI platform delivery:
Lead delivery of production-ready AI platform capabilities, including LLM integration, RAG systems, and agentic workflows.MLOps and LLMOps practices:
Establish production-grade MLOps and LLMOps capabilities, including CI/CD, model lifecycle governance, monitoring, and evaluation. Enterprise standards andResponsible AI:
Ensure AI engineering platforms meet enterprise expectations for security, privacy, compliance, and Responsible AI.Secure-by-default engineering:
Embed secure-by-default practices across AI and engineering workflows, including application security, threat modeling, and policy enforcement.Governance and risk partnership:
Partner with CISO and risk leadership to define governance expectations, strengthen control alignment, and manage high-risk releases. Cross- functional alignment: Drive alignment across engineering, product, platform, and security teams to ensure shared priorities, clear decision-making, and coordinated execution.
Organization building:
Build and scale a high-performing engineering organization through hiring, rotation planning, leadership development, and capability growth.Dependency management:
Resolve cross-team dependencies through lateral alignment, shared accountability, and proactive escalation management.Required Qualifications Engineering leadership:
Proven track record leading multi-team platform or AI engineering organizations at Director+ scope.Domain depth and breadth:
Deep expertise in at least two domains, such as Developer Experience Engineering, Software Engineering in Test, SRE/Observability, or Application Security, with working fluency across the others.Production AI delivery:
Hands-on experience building and scaling production AI/ML systems, including LLMs, ML pipelines, or AI platforms.Cloud-native architecture:
Strong understanding of cloud-native architecture such as Azure, AWS, or GCP and single or multi cloud design and deployment AI lifecycle governance: Experience implementing MLOps, LLMOps, and AI lifecycle governance practices. Security, privacy, and compliance: Strong understanding of secure SDLC, data privacy, and compliance requirements as well as fluency in AI and LLM emerging security challenges.Technical risk leadership:
Ability to operate as a peer to security leadership and own technical risk conversations.Experience level:
Minimum 20+ years of engineering experience, including at least 8 years leading teams at Director+ scope. Preferred Qualifications Enterprise AI platform experience: Experience building enterprise AI platforms or scaling enterprise engineering organizations.Responsible AI and regulatory fluency:
Familiarity with Responsible AI frameworks, such as NIST AI RMF, and related regulatory expectations.Agentic architecture exposure:
Experience with multi-agent architectures, orchestration layers, or model routing.Regulated industry experience:
Experience operating in regulated industries, such as financial services, insurance, or healthcare.Platform adoption leadership:
Experience managing platform adoption and internal developer experience programs.Leadership Expectations Strategic systems thinking:
Translate AI opportunities into enterprise-scale platforms that advance engineering productivity, quality, and reliability.Innovation with discipline:
Balance speed of innovation with governance, security, and operational rigor.Team leadership and culture:
Build high-performing teams with strong accountability, engineering excellence, and continuous improvement practices.Executive communication and alignment:
Communicate effectively with executive stakeholders and drive alignment across enterprise priorities.Operational execution:
Maintain rigor across delivery planning, prioritization, execution tracking, and outcomes management. #LI-DW1Base Pay Range:
The base pay range noted represents the company's good faith minimum and maximum range for this role at the time of posting. The actual compensation offered to a candidate will be dependent upon several factors, including but not limited to experience, qualifications and geographic location. Also, most employees are eligible for additional incentive pay. $203,760.00- $249,040.