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# AI Enablement and Developer Experience

- **Company:** LPL Financial
- **Location:** Fort Mill, SC, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $115,141.0 - $191,902.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, Software Debugging, Programming Tools, Python (Programming Language), Machine Learning, Software Engineering, Backend, Information Technology
- **Published:** June 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=52f7651e1bd46b14

## About the Role

Do you have experience in Software engineering?, * Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

 * 7-12 years experience developing backend services, APIs, or developer platforms. Preferred Python or Java
 * 7-12 years experience creating reusable libraries, SDKs, templates, or internal frameworks used by other engineers
 * 2-3 years working knowledge of AI or machine-learning-powered application development

Core Competencies

 * Developer enablement and platform thinking
 * Problem solving and systems design
 * Collaboration across engineering and product teams
 * Continuous learning and improvement
 * Focus on usability, reliability, and scalability

Please note: This position does not offer work authorization sponsorship now or in the future. Applicants must have valid U.S. work authorization that does not require employer sponsorship.

## Description

* Build reusable SDKs, sample applications, and reference implementations to support AI-enabled software development
 * Create developer tooling that supports local development, testing, evaluation, debugging, and deployment of AI workloads
 * Translate platform capabilities into clear technical documentation, implementation guides, and onboarding resources
 * Develop templates and examples for common AI use cases such as chat assistants, summarization, retrieval-augmented generation (RAG), and agent-based workflows
 * Partner with product and engineering teams to support adoption and promote consistent, scalable AI solutions
 * Gather feedback from early adopters and continuously improve tools, documentation, and the overall developer experience
 * Support internal demos, workshops, hackathons, and innovation initiatives that showcase AI capabilities

What Success Looks Like

 * Engineers can quickly get started building AI solutions without needing deep platform expertise
 * AI capabilities are easier to use, easier to understand, and trusted by development teams
 * Reusable patterns reduce duplicated effort and improve consistency and quality across teams


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