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LF
Lincoln Financial
Sr. Analyst, Applied AI Engineer
Career Insights for Artificial Intelligence Engineer (General)
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Based on Pennsylvania 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.
$132,288 / year median in Pennsylvania
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 #: 76387 The Role at a Glance The Sr. Applied AI Engineer designs and builds intelligent services and agentic workflows that sit on top of the cloud, data, and application stack. This role creates production-ready solutions for ranking, summarization, retrieval, classification, recommendation, and decision support using Python and governed enterprise AI development practices. What you'll be doing Leads the design and implementation of AI solutions for ranking, summarization, extraction, classification, recommendation, and conversational workflows across complex or multi-stakeholder use cases. Develops prompt-based and model-based solutions using Python and modern AI orchestration patterns, independently evaluating technical options and recommending scalable approaches. Works across structured and unstructured data in cloud and enterprise data environments to design reliable, governed AI workflows that integrate with broader data and application ecosystems. Establishes and enhances evaluation, testing, and monitoring approaches for AI-enabled workflows and agentic systems to improve accuracy, quality, reliability, and operational readiness. Partners with business, engineering, product, and governance stakeholders to translate ambiguous operational pain points into production AI features, success measures, and implementation plans. Advances reusable prompt libraries, agent patterns, and service interfaces for internal AI products, promoting consistency, scalability, and adoption across teams. Applies and helps strengthen responsible AI practices, including grounding, escalation paths, review controls, policy constraints, and measurable success criteria for AI-enabled solutions. Provides technical guidance to peers and project teams by sharing best practices, reviewing solution approaches, and influencing adoption of effective AI engineering patterns. What we're looking for- 4 Year/Bachelor's degree or equivalent work experience (4 years of experience in lieu of Bachelor's)
- 5 - 7+ Years of experience in ML engineering, applied
AI, NLP, LLM
engineering, that directly aligns with the specific responsibilities for this position. 5+ years of experience in ML engineering, appliedAI, NLP, LLM
engineering, or a related field.- Strong Python experience.
- Experience productionizing AI or ML workflows on AWS or similar cloud platforms.
- Familiarity with Databricks, MLflow, model evaluation, and governed data environments.
- Experience working with SQL and distributed processing tools such as PySpark.
- Experience with SageMaker Studio, AgentCore are plus
- Strong communication and product collaboration skills.