AI Engineer

Job Title: AI Engineer

Location: Coppell, Texas

Work Arrangement: On-Site

Job Summary

We are seeking an AI Engineer to join our engineering team and support AI-driven transformation initiatives within the pharmaceutical industry. The ideal candidate will design, develop, and test AI-powered solutions using AWS AI services, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and advanced prompt engineering techniques.

The AI Engineer will work closely with product, design, and engineering teams to develop effective AI workflows, optimize prompts, and integrate local files, documents, and enterprise data sources into AI-powered applications. This role will also focus on AI performance evaluation, security testing, and governance to ensure reliable, secure, and responsible AI implementation.

Key Responsibilities

• Develop and maintain a structured prompt library for common use cases, including summarization, question answering, information extraction, code generation, and file analysis.
• Apply advanced prompt engineering techniques, including few-shot prompting, role specification, and structured input formats, to improve AI output quality.
• Design and implement RAG pipelines that connect enterprise systems such as Warehouse Management Systems (WMS), Electronic Data Interchange (EDI) logs, Standard Operating Procedures (SOPs), contract repositories, and other data sources.
• Develop, deploy, and optimize LLM-powered applications, including internal knowledge assistants and client-facing chat solutions.
• Extend AI-powered response repositories and identify opportunities to automate workflows, improve processes, and enhance system performance.
• Conduct A/B testing of prompt variations, evaluate AI-generated responses, and document performance benchmarks.
• Work with Claude Desktop and similar AI tools to support document-based workflows involving PDFs, Word documents, spreadsheets, and code files.
• Create reusable prompt patterns for multi-file inputs, long-context documents, and structured data analysis.
• Develop and maintain internal tools for prompt evaluation, testing, and performance monitoring.
• Test AI workflows for vulnerabilities, potential bias, and misuse risks while supporting AI safety, security, and governance requirements.
• Collaborate with cross-functional teams and provide guidance to end users on effective AI tools and prompt usage.

Required Skills

• Experience with Generative AI, Large Language Models (LLMs), and AI application development.
• Hands-on experience with AWS AI services and cloud-based AI solutions.
• Strong understanding of prompt engineering, prompt optimization, and LLM evaluation techniques.
• Experience designing and developing Retrieval-Augmented Generation (RAG) pipelines.
• Knowledge of enterprise data integration and document-processing workflows.
• Familiarity with Claude Desktop or similar AI tools for document analysis and file-based workflows.
• Experience with AI testing, performance benchmarking, and prompt evaluation.
• Understanding of AI security, data privacy, responsible AI practices, and governance.
• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience working with WMS, EDI systems, SOP repositories, contract data, or enterprise knowledge bases.
• Familiarity with Python, APIs, vector databases, embeddings, and document-processing frameworks.
• Experience developing AI assistants, enterprise chatbots, or automated document-analysis solutions.
• Exposure to pharmaceutical, biotechnology, life sciences, or other regulated industry environments.