Engineer - Digital Integration - Wood

Key Responsibilities

• Design, develop, and deploy end‑to‑end AI applications, ensuring production readiness and scalability.
• Build and expose RESTful APIs and microservices that integrate AI functionalities into existing digital workflows.
• Implement robust data ingestion, extraction (including OCR), and preprocessing pipelines for both structured and unstructured data.
• Develop and maintain vector databases, embedding pipelines, and chunking strategies to enable efficient semantic search and retrieval.
• Build and fine‑tune large language model (LLM) solutions using Prompt Engineering, Retrieval‑Augmented Generation (RAG) architectures, and custom fine‑tuning techniques.
• Collaborate with cross‑functional teams to translate business requirements into technical specifications and deliver high‑quality AI solutions.

• Proficiency in Python and experience building production‑grade AI services.
• Strong background in machine learning, including model training, evaluation, and deployment.
• Hands‑on experience with RESTful API design, microservices, and containerization.
• Knowledge of OCR technologies, vector databases (e.g., Pinecone, Milvus), and semantic retrieval pipelines.
• Experience with Prompt Engineering, RAG, and LLM fine‑tuning.