Sr. Digital Delivery Specialist

Role overview

Core responsibilities

• Identify and prioritize high-impact AI/ML use cases with business stakeholders and subject-matter experts.
• Build enterprise GenAI assistants, RAG and document-intelligence solutions, and autonomous multi-agent workflows.
• Deliver industrial AI for process optimization, maintenance, quality, energy, yield, and anomaly detection.
• Develop AI digital twins and computer-vision applications for plant operations, inspection, safety, and automation.
• Develop and optimize machine-learning models; implement MLOps pipelines, deployment, monitoring, drift detection, and retraining.
• Build scalable Databricks pipelines and integrate solutions with Microsoft Azure and Dataiku.
• Own projects from proof of concept through production, ensuring quality, security, performance, and timely delivery.
• Support user adoption through application integration, SOP updates, training, and change management.
• Establish responsible-AI governance and safeguards; contribute to architecture, standards, innovation pilots, mentoring, and communication of business impact.

Required technical capabilities

• Hands-on machine learning, deep learning, statistical modeling, Python, and SQL.
• GenAI/LLMs, prompt engineering, RAG, embeddings, vector databases, and fine-tuning.
• Agentic AI and multi-agent/A2A systems; example frameworks include LangChain, LangGraph, Semantic Kernel, and AutoGen.
• Industrial AI, AI digital twins, and computer vision, including OpenCV, PyTorch/TensorFlow, and detection or segmentation.
• MLOps including MLflow, deployment, Docker/Kubernetes, CI/CD, GitHub Actions, and model monitoring.
• Databricks, Spark, Delta Lake, Unity Catalog, and notebooks; Microsoft Azure AI services and Dataiku.
• Responsible-AI governance, evaluation, guardrails, and LLMOps.

Minimum requirements

• Bachelor’s or master’s degree in Computer Science, Data Science, AI, Statistics, Engineering, Physics, or Mathematics.
• 4+ years in data science or machine-learning delivery and 2+ years implementing cutting-edge AI/GenAI technologies.
• Demonstrated production delivery of GenAI or agentic solutions.
• Exposure to manufacturing, heavy industry, or steel operations.
• Experience with responsible-AI governance and LLMOps.
• AI/ML, Databricks, Microsoft Azure AI, or Dataiku certifications.
• Ability to translate business problems into technical solutions; strong communication, problem-solving, stakeholder-management, and collaboration skills.

Additional contributions