AI Engineer

Job Title: AI Engineer

Duration: 6-12 month contract

Mode: Onsite 5days per week

Location : 3100 Olympus Blvd, Suite 100, COPPELL, Texas 75019, United States

Job Description:

The AI Engineer is a key contributor within a lean, high-impact transformational team at a pharma-focused third-party logistics provider serving 90+ clients. You will join our engineering team and serve as the bridge between our AI capabilities and our end users. In this role, you will design and test AWS AI based solutions and optimize prompt strategies that help users unlock the full potential of AI and Claude Desktop - including seamless integration of local files, documents, and data sources into AI-powered workflows.

You will work closely with product and design teams to build a library of high-quality prompts, develop internal tooling for prompt evaluation, and directly support users in crafting effective instructions for complex, document-heavy tasks. You will also own safety and governance responsibilities to proactively stress-test prompts and file-based workflows for vulnerabilities, bias, and misuse risks before they reach production.

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.