AI Engineer

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.