3+ years in software engineering or applied AI, with 1 year in LLM prompt engineering.
Hands-on experience with Claude, GPT-4, or similar LLMs in production settings.
Background in technical writing, UX design, or developer advocacy.
Expertise in prompt engineering disciplines like system prompt design and output validation.
Experience with adversarial prompt testing and AI safety evaluations.
Production deployment mindset with emphasis on monitoring, uptime, and latency management.
Experience in regulated industries like pharma or financial services is preferred.
Responsibilities
Establish and manage a structured prompt library for common use cases.
Apply advanced prompting techniques using methods like chain-of-thought and few-shot examples.
Design and build RAG pipelines connecting various internal systems.
Deploy and optimize LLM applications including internal and client-facing solutions.
Continuously A/B test prompt variants and document performance metrics.
Act as the subject-matter expert on file-handling capabilities for Claude Desktop.
Create reusable prompt patterns for multi-file and structured data inputs.
Benefits
Collaborative work environment with opportunities to influence company AI solutions.
Exposure to cutting-edge technologies in AI and prompt engineering.
Opportunity to work with a lean team in a regulated industry, enhancing compliance knowledge.
Professional development through cross-functional collaboration and training.
Full Job Description
Responsibilities
Establish and maintain a structured prompt library for the company which will cover common use cases (summarization, Q&A, extraction, code generation, file analysis).
Apply advanced prompting techniques including chain-of-thought, few-shot examples, role specification, and XML-structured inputs.
Design and build RAG pipelines connecting our WMS, EDI logs, SOP repositories, contract data, and other systems.
Deploy and tune LLM-powered applications including internal knowledge assistants, client-facing chat, extend RAG based response repositories, and leverage AI to optimize workflows, processes, and drive system improvements.
Continuously A/B test prompt variants and document performance benchmarks.
Serve as the subject-matter expert on Claude Desktop's file-handling capabilities, including referencing local PDFs, Word documents, spreadsheets, and code files within prompts.
Create reusable prompt patterns that work reliably with multi-file inputs, long-context documents, and structured data.
Champion prompt engineering best practices across internal teams including Operations, Control Tower, Business segments, and General Counsel to translate business problems into AI solutions.
Embed PII handling rules, data residency constraints, jailbreak resistance, and refusal behavior guardrails into production prompt workflows.
Test for prompt injection risks specific to local file inputs - including malicious content embedded in PDFs, DOCX, or CSV files uploaded through Claude Desktop.
Build and maintain internal evaluation harnesses to measure prompt quality, consistency, and regression over model updates.
Other duties as assigned
Qualifications and Job Specifications
3+ years of software engineering or applied AI experience, with at least 1 year focused on LLM prompt engineering.
Deep hands-on experience with Claude, GPT-4, or similar large language models in production or near-production settings.
Background in technical writing, UX wireframing, instructional design, or developer advocacy.
Prompt engineering discipline including system prompt design, zero-shot, few-shot, output validation, hallucination mitigation.
Experience with adversarial prompt testing, red teaming methodologies, or AI safety evaluation frameworks.
Production deployment mindset. You monitor what you build, you own uptime, you care about latency and cost.
Previous experience working with a lean team in a regulated industry, such as pharma, healthcare, government, or financial services is preferred.
Excellent written communication skills; ability to translate complex technical concepts for non-technical audiences.
Proven ability to collaborate cross-functionally across engineering, product, and customer-facing teams.
Technical Expertise
Direct experience with Claude Desktop, including MCP (Model Context Protocol) server configuration and local file tooling.
Familiarity with RAG (Retrieval-Augmented Generation) architecture and vector databases (e.g., Pinecone, Weaviate, pgvector).
Proficiency in Python or JavaScript for building prompt pipelines, evaluation scripts, and automation tooling.
Supply chain, logistics, or 3PL domain knowledge including WMS, EDI 850/810/856, DSCSA familiarity.
Knowledge with Intelligent Document Processing (IDP), OCR pipelines, and handwritten text extraction (AWS Textract, CargoShot, or equivalent).
Exposure to government or enterprise RFP processes, understanding of compliance documentation, and proposal requirements are nice to have.
Additional Employment Requirements
Must be able to successfully pass all preliminary employment requirements (i.e., background check and drug screen)
Other requirements such as professional licensing.
Physical/Mental/Visual Demands
Work is light to medium in nature with frequent walking to perform assigned tasks.
Work is performed in office.
Must be able to safely conduct occasional lifting of 25 lbs.
