Sr. Director, AI-Native Intelligence & Data Insights

The Role at a Glance

Lincoln Financial Group is building an AI Native Intelligence platform that turns enterprise data — starting with call center audio and transcripts, and expanding to claims, policy, and underwriting data — into a conversational, agentic layer the business can query directly. Instead of static reports, the platform is designed to let business users ask natural-language questions and get grounded, cited answers, backed by a real semantic understanding of Lincoln's data.

We're looking for a Senior Director to own the architecture and technical delivery of this platform end to end. This is a hands-on, builder-leader role: someone who sets the technical vision and roadmap, but who is equally comfortable reviewing a Bedrock agent's tool-calling logic, debugging a Step Functions pipeline, or sketching a knowledge graph schema on a whiteboard. You'll build and lead the team that takes this from pilot to enterprise scale.

What you'll be doing

• Own the end-to-end architecture for the AI Native Intelligence platform on AWS — ingestion, enrichment, the semantic/business ontology layer, retrieval-augmented generation (RAG), knowledge graphs, and agentic orchestration (Amazon Bedrock, Bedrock AgentCore, Amazon Neptune, OpenSearch Serverless, AWS Glue, Amazon Transcribe/Comprehend, and related services).
• Translate diverse enterprise datasets — call center transcripts and audio, policy administration, claims, underwriting — into a unified, governed data and semantic foundation that supports natural-language querying and analytics.
• Design and evolve the business ontology, knowledge graph, and KPI/metrics glossary that ground the platform's AI in Lincoln's own business definitions, so answers are accurate and consistent with how the business already measures itself.
• Lead build-vs-buy decisions across the AI/ML and data stack, and stay ahead of a fast-moving AWS AI landscape — model updates, agent frameworks, vector and graph databases, evaluation tooling.
• Build, mentor, and scale a team of engineers, data scientists, and architects; set technical standards, run design/architecture reviews, and unblock hard technical problems.
• Partner directly with business stakeholders — call center operations, claims, underwriting, compliance — to identify high-value insight use cases and translate them into technical requirements and delivery plans.
• Establish guardrails, governance, and responsible-AI practices: PII handling and redaction, model evaluation, hallucination mitigation, human-in-the-loop review, and auditability.
• Define and track success metrics for AI initiatives — retrieval/insight accuracy, adoption, time-to-insight, and cost-to-serve — and report progress to senior and executive leadership.
• Stay technically hands-on: prototype new capabilities, review code and architecture, and work directly alongside the team rather than directing from a distance.

What we’re looking for

• 12+ years of experience in data engineering, ML/AI engineering, or applied data science, including 5+ years in a technical leadership role (Director, Senior Manager, or Principal Architect) building production data or AI platforms.
• Deep, hands-on experience with AWS data and AI services: S3, Glue, Lambda, Step Functions, Amazon Bedrock (or an equivalent enterprise LLM platform), OpenSearch or another vector database, and a graph database such as Amazon Neptune.
• Proven experience building or leading RAG, agentic AI, or conversational AI systems in production — not just proofs of concept.
• Strong grasp of data modeling, semantic layers, business ontologies, and knowledge graphs, and how they ground LLM-based systems in accurate, consistent business meaning.
• A track record of building, mentoring, and scaling high-performing technical teams. Excellent communication skills — able to explain architecture trade-offs to engineers and business impact to executives with equal clarity.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience; advanced degree a plus.

Preferred

• Experience with speech-to-text and NLP pipelines (e.g., Amazon Transcribe, Amazon Comprehend), particularly for audio or call center data.
• Experience in insurance, financial services, or another regulated industry, with a working understanding of data privacy, PII, and regulatory compliance.
• Familiarity with call center analytics, claims processing, or policy administration data.
• Experience establishing responsible-AI governance frameworks — bias mitigation, hallucination controls, model evaluation, and audit trails.
• Contributions to open-source AI/data tooling, patents, or published technical work.

Application Deadline

Applications for this position will be accepted through November 30, 2026, subject to earlier closure due to applicant volume.

What’s it like to work here?

At Lincoln Financial, we love what we do. We make meaningful contributions each and every day to empower our customers to take charge of their lives. Working alongside dedicated and talented colleagues, we build fulfilling careers and stronger communities through a company that values our unique perspectives, insights and contributions and invests in programs that empower each of us to take charge of our own future.

What’s in it for you:

Clearly defined career tracks and job levels, along with associated behaviors for each of Lincoln's core values and leadership attributes

Leadership development and virtual training opportunities

PTO/parental leave

Competitive 401K and employee benefits

Free financial counseling, health coaching and employee assistance program

Tuition assistance program

Work arrangements that work for you

Effective productivity/technology tools and training

The pay range for this position is with anticipated pay for new hires between the minimum and midpoint of the range and could vary above and below the listed range as permitted by applicable law. Pay is based on non-discriminatory factors including but not limited to work experience, education, location, licensure requirements, proficiency and qualifications required for the role. The base p