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Senior Director, AI Native Analytics
Radnor, PA, US
Actively hiring, first seen by us 19 hours ago- Pay
$171,375–274,200/yearAnnual period assumed. Location-specific pay — pay source
Effective productivity/technology tools and training The pay range for this position is $171,375 - $274,200 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 pay is just one component of Lincoln’s total rewards package for employees. In addition, the role may be eligible for the Annual Incentive Program, which is discretionary and based on the performance of the company, business unit and individual. Other rewards may include long-term incentives, sales incentives and Lincoln’s standard benefits package. About The Company
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and build conversational AI over Bedrock Agents, RAG, NL-to-SQL and knowledge graph queries
Build capabilities that detect patterns, trends, and anomalies across enterprise data proactively
Build and tune AI extraction pipelines that turn unstructured data into query-ready facts
Own prompt engineering, agent tool design, and model selection
Build evaluation processes and regression checks for LLM-based systems
From the employer’s posting
Design and build the conversational AI experience end to end
Build capabilities that continuously detect patterns, trends, and anomalies across enterprise data
Build and tune the AI extraction pipeline that turns raw unstructured data
Own prompt engineering and agent tool design
Build evaluation and quality processes for LLM-based systems
Education & alternatives
- Clear communicator who can demo a working system to engineers and explain its behavior and limitations to non-technical business stakeholders with equal clarity. - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Nice to Haves:
About Lincoln Financial
Lincoln Financial (NYSE: LNC) helps people to confidently plan for their version of a successful future.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 11, 2026today
- Recorded sightings
- 2
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Lincoln Financial is hiring
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- TypeScript
- AWS
- DynamoDB
- Redshift
- S3
- Node.js
Where the posting names them
- Experience building or applying pattern-, trend-, or anomaly-detection techniques over enterprise data (statistical, ML-based, or LLM-assisted), and turning what's found into something a business user can act on. - Strong proficiency in Python and/or TypeScript/Node.js for building extraction pipelines, agent tools, and integration code. - Working knowledge of SQL and cloud analytics engines (Athena, Redshift, or similar), sufficient to design and validate natural-language-to-SQL experiences.
What you'll be doing - Design and build the conversational AI experience end to end: Bedrock Agents (via AgentCore or MCP/API), retrieval-augmented generation over Bedrock Knowledge Bases / OpenSearch Serverless, natural-language-to-SQL over Athena, and relationship queries over a knowledge graph (Amazon Neptune / GraphRAG). - Build capabilities that continuously detect patterns, trends, and anomalies across enterprise data — surfacing what's notable proactively, rather than waiting for someone to know what question to ask.
- Strong proficiency in Python and/or TypeScript/Node.js for building extraction pipelines, agent tools, and integration code. - Working knowledge of SQL and cloud analytics engines (Athena, Redshift, or similar), sufficient to design and validate natural-language-to-SQL experiences. - Clear communicator who can demo a working system to engineers and explain its behavior and limitations to non-technical business stakeholders with equal clarity.
The Role at a Glance Lincoln Financial Group is building an AI Native Intelligence platform that turns enterprise data into a conversational, agentic layer the business can query directly — and that continuously finds patterns, trends, and anomalies in that data on its own. The platform's architecture spans an AWS-native ingestion and extraction pipeline, a governed semantic layer and business knowledge graph, and an intelligence layer that answers questions in plain language and surfaces what's changing, instead of relying on static reports someone has to remember to check. We're looking for a Sr. Director, AI Native Analytics to be the hands-on builder of that conversational and analytical experience: the person who actually designs and ships the Bedrock agents, retrieval pipelines, pattern-detection logic, and natural-language-to-analytics capabilities that make the platform usable. This is an individual-contributor-heavy, deeply technical role — you'll spend most of your time in the architecture, the prompts, and the code, while partnering closely with the Senior Director on direction and with business stakeholders on what “useful” actually looks like.
- Mentor and provide technical direction to engineers contributing to the conversational AI workstream, and represent this workstream in architecture reviews led by the Senior Director. - Stay current with the fast-moving AWS AI landscape — Bedrock model and AgentCore updates, new retrieval and evaluation tooling — and bring concrete recommendations back to the team. What we’re looking for
- 8+ years of experience in Data Analytics / Business Intelligence with at least 2+ years building production LLM-based Analytics systems (not just prototypes or proofs of concept). - Hands-on, production-level expertise with the AWS AI/data stack: Amazon Bedrock (Knowledge Bases, Agents/AgentCore), AWS Lambda, Step Functions, Amazon S3, AWS Glue, and Amazon Athena; working experience with a vector store (OpenSearch Serverless or similar). - Strong, practical prompt-engineering and LLM application development skills: structured extraction, tool-calling/agentic patterns, retrieval design, and iterative evaluation against real questions.
- Build capabilities that continuously detect patterns, trends, and anomalies across enterprise data — surfacing what's notable proactively, rather than waiting for someone to know what question to ask. - Build and tune the AI extraction pipeline that turns raw unstructured data (documents, logs, notes, communications) into structured, query-ready facts — using Amazon Comprehend and/or LLM-based extraction via the Bedrock Converse API (Lambda, Step Functions, DynamoDB for state). - Own prompt engineering and agent tool design: system instructions, tool/action-group definitions, structured-output schemas, and model selection/tiering to balance accuracy, latency, and cost.
Your next step
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About Lincoln Financial
- People
- About 9,981 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as LNC.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
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About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Alternate Locations: Radnor, PA (Pennsylvania); Charlotte, NC (North Carolina); Fort Wayne, IN (Indiana); Greensboro, NC (North Carolina)
Work Arrangement:
Hybrid : Employee will work 3 days a week in a Lincoln office
Relocation assistance: is not available for this opportunity.
Requisition #: 76794
The Role at a Glance
Lincoln Financial Group is building an AI Native Intelligence platform that turns enterprise data into a conversational, agentic layer the business can query directly — and that continuously finds patterns, trends, and anomalies in that data on its own. The platform's architecture spans an AWS-native ingestion and extraction pipeline, a governed semantic layer and business knowledge graph, and an intelligence layer that answers questions in plain language and surfaces what's changing, instead of relying on static reports someone has to remember to check.
We're looking for a Sr. Director, AI Native Analytics to be the hands-on builder of that conversational and analytical experience: the person who actually designs and ships the Bedrock agents, retrieval pipelines, pattern-detection logic, and natural-language-to-analytics capabilities that make the platform usable. This is an individual-contributor-heavy, deeply technical role — you'll spend most of your time in the architecture, the prompts, and the code, while partnering closely with the Senior Director on direction and with business stakeholders on what “useful” actually looks like.
What you'll be doing
- Design and build the conversational AI experience end to end: Bedrock Agents (via AgentCore or MCP/API), retrieval-augmented generation over Bedrock Knowledge Bases / OpenSearch Serverless, natural-language-to-SQL over Athena, and relationship queries over a knowledge graph (Amazon Neptune / GraphRAG).
- Build capabilities that continuously detect patterns, trends, and anomalies across enterprise data — surfacing what's notable proactively, rather than waiting for someone to know what question to ask.
- Build and tune the AI extraction pipeline that turns raw unstructured data (documents, logs, notes, communications) into structured, query-ready facts — using Amazon Comprehend and/or LLM-based extraction via the Bedrock Converse API (Lambda, Step Functions, DynamoDB for state).
- Own prompt engineering and agent tool design: system instructions, tool/action-group definitions, structured-output schemas, and model selection/tiering to balance accuracy, latency, and cost.
- Integrate the conversational layer with the platform's semantic layer and business ontology (KPI and metrics definitions, business rules glossary) so agent answers stay consistent with how the business already measures itself — never computing an ad hoc number that disagrees with a dashboard.
- Build evaluation and quality processes for LLM-based systems: golden question sets, retrieval/accuracy scoring, hallucination and abstention testing, and regression checks before any change ships to users.
- Implement guardrails in partnership with security/compliance: PII detection and redaction, Bedrock Guardrails configuration, access-controlled data zones, and audit logging for every AI-generated answer.
- Partner directly with business stakeholders across the enterprise to translate real questions into working conversational and pattern-detection features, and iterate quickly based on usage and accuracy feedback.
- Mentor and provide technical direction to engineers contributing to the conversational AI workstream, and represent this workstream in architecture reviews led by the Senior Director.
- Stay current with the fast-moving AWS AI landscape — Bedrock model and AgentCore updates, new retrieval and evaluation tooling — and bring concrete recommendations back to the team.
What we’re looking for
Must Haves:
- 8+ years of experience in Data Analytics / Business Intelligence with at least 2+ years building production LLM-based Analytics systems (not just prototypes or proofs of concept).
- Hands-on, production-level expertise with the AWS AI/data stack: Amazon Bedrock (Knowledge Bases, Agents/AgentCore), AWS Lambda, Step Functions, Amazon S3, AWS Glue, and Amazon Athena; working experience with a vector store (OpenSearch Serverless or similar).
- Strong, practical prompt-engineering and LLM application development skills: structured extraction, tool-calling/agentic patterns, retrieval design, and iterative evaluation against real questions.
- Solid understanding of semantic layers, business ontologies, or metrics layers, and how to ground LLM outputs in governed, consistent business definitions rather than ad hoc computation.
- Experience building or applying pattern-, trend-, or anomaly-detection techniques over enterprise data (statistical, ML-based, or LLM-assisted), and turning what's found into something a business user can act on.
- Strong proficiency in Python and/or TypeScript/Node.js for building extraction pipelines, agent tools, and integration code.
- Working knowledge of SQL and cloud analytics engines (Athena, Redshift, or similar), sufficient to design and validate natural-language-to-SQL experiences.
- Clear communicator who can demo a working system to engineers and explain its behavior and limitations to non-technical business stakeholders with equal clarity.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice to Haves:
- Experience with GraphRAG or other knowledge-graph-grounded retrieval patterns, and with a graph database such as Amazon Neptune.
- Experience with a semantic-layer/metrics-layer tool (e.g., Cube.dev) used to serve consistent metrics to both BI and AI consumers.
- Experience with NLP/document-processing pipelines (e.g., Amazon Comprehend) for extracting structure from varied unstructured enterprise data.
- Experience in insurance, financial services, or another regulated industry, with a working understanding of PII handling and data privacy/compliance considerations.
- Experience configuring LLM safety/evaluation tooling such as Bedrock Guardrails, or building your own evaluation harness for generative AI systems.
- Familiarity with a range of enterprise data domains (financial, operational, customer, or workforce data) within a large organization.
Application Deadline
Applications for this position will be accepted through January 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
-
Free financial counseling, health coaching and employee assistance program
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Tuition assistance program
-
Work arrangements that work for you
-
Effective productivity/technology tools and training
The pay range for this position is $171,375 - $274,200 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 pay is just one component of Lincoln’s total rewards package for employees. In addition, the role may be eligible for the Annual Incentive Program, which is discretionary and based on the performance of the company, business unit and individual. Other rewards may include long-term incentives, sales incentives and Lincoln’s standard benefits package.
About The Company
Lincoln Financial (NYSE: LNC) helps people to confidently plan for their version of a successful future. We focus on identifying a clear path to financial security, with products including annuities, life insurance, group protection, and retirement plan services.
With our 120-year track record of expertise and integrity, millions of customers trust our solutions and service to help put their goals in reach.
Lincoln Financial Distributors, a broker-dealer, is the wholesale distribution organization of Lincoln Financial. Lincoln Financial is the marketing name for Lincoln Financial Corporation and its affiliates including The Lincoln National Life Insurance Company, Fort Wayne, IN, and Lincoln Life & Annuity Company of New York, Syracuse, NY. Lincoln Financial affiliates, their distributors, and their respective employees, representatives and/or insurance agents do not provide tax, accounting or legal advice.
Lincoln is committed to creating an inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Follow us on Facebook, X, LinkedIn, Instagram, and YouTube. For the latest company news, visit our newsroom.
Be Aware of Fraudulent Recruiting Activities
If you are interested in a career at Lincoln, we encourage you to review our current openings and apply on our website. Lincoln values the privacy and security of every applicant and urges all applicants to diligently protect their sensitive personal information from scams targeting job seekers. These scams can take many forms including fake employment applications, bogus interviews and falsified offer letters.
Lincoln will not ask applicants to provide their social security numbers, date of birth, bank account information or other sensitive information in job applications. Additionally, our recruiters do not communicate with applicants through free e-mail accounts (Gmail, Yahoo, Hotmail) or conduct interviews utilizing video chat rooms. We will never ask applicants to provide payment during the hiring process or extend an offer without conducting a phone, live video or in-person interview. Please contact Lincoln's fraud team at fraudhotline@lfg.com if you encounter a recruiter or see a job opportunity that seems suspicious.
Additional Information
This position may be subject to Lincoln’s Political Contribution Policy. An offer of employment may be contingent upon disclosing to Lincoln the details of certain political contributions. Lincoln may decline to extend an offer or terminate employment for this role if it determines political contributions made could have an adverse impact on Lincoln’s current or future business interests, misrepresentations were made, or for failure to fully disclose applicable political contributions and or fundraising activities.
Any unsolicited resumes or candidate profiles submitted through our web site or to personal e-mail accounts of employees of Lincoln Financial are considered property of Lincoln Financial and are not subject to payment of agency fees.
Lincoln Financial ("Lincoln" or "the Company") is an Equal Opportunity employer and, as such, is committed in policy and practice to recruit, hire, compensate, train and promote, in all job classifications, without regard to race, color, religion, sex, age, national origin or disability. Opportunities throughout Lincoln are available to employees and applicants are evaluated on the basis of job qualifications. If you are a person with a disability that impedes your ability to express your interest for a position through our online application process, or require TTY/TDD assistance, contact us by calling (866) 922-6543.
This Employer Participates in E-Verify. See the E-Verify notices.
Este Empleador Participa en E-Verify. Ver el E-Verify avisos.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Effective productivity/technology tools and training The pay range for this position is $171,375 - $274,200 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 pay is just one component of Lincoln’s total rewards package for employees. In addition, the role may be eligible for the Annual Incentive Program, which is discretionary and based on the performance of the company, business unit and individual. Other rewards may include long-term incentives, sales incentives and Lincoln’s standard benefits package. About The Company
- Location & working pattern
Radnor, PA, US
Work Arrangement: Hybrid : Employee will work 3 days a week in a Lincoln office Relocation assistance: is not available for this opportunity.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.