AI/ML Engineer III, Enterprise AI

Adusa; Chicago (IL); Hybrid; USD 125,000 - 188,000; Full time

Job summary

Ahold Delhaize USA is seeking an AI/ML Engineer III to advance enterprise AI initiatives. You will design and scale generative AI, retrieval-based systems, and agentic workflows in collaboration with data scientists and engineers.

You will develop RAG pipelines, deploy LLM-powered chatbots, and lead model-serving solutions using REST microservices. A hybrid work model with in-person and remote days is offered.

Qualifications

• Advanced degree or equivalent in data science/CS.
• 5+ years AI/ML engineering experience.
• Strong coding in Python and ML libraries.
• Hands-on in RAG, embeddings, indexing, retrieval.
• Experience with LLM-powered apps and AI agents.
• Familiarity with API design and agile methods.

Responsibilities

• Explore Generative AI and RAG for enterprise use cases.
• Design agentic AI solutions and architectures.
• Develop RAG pipelines with embeddings, indexing, retrieval.
• Build AI-powered chatbots and conversational apps with LLMs.
• Evaluate new AI techniques for scalability and reliability.
• Develop model-serving REST microservices and pipelines.
• Collaborate with data partners and product teams.
• Stay updated on AI trends and best practices.
• Support on-call incidents as needed.

Skills

Python

Agentic AI

Deep learning

LLM development

REST microservices

PyTorch

TensorFlow

Hugging Face

Data structures

Algorithms

Communication skills

Education

Master's degree or PhD in Data Science or related field

Tools

Azure

Databricks

Kafka

Kubernetes

Job description

Introduction

Ahold Delhaize USA, a division of global food retailer Ahold Delhaize, is part of the U.S. family of brands, which also includes five leading omnichannel grocery brands – Food Lion, Giant Food, The GIANT Company, Hannaford and Stop & Shop. Ahold Delhaize USA associates support the brands with a wide range of services, including Finance, Legal, Sustainability, Commercial, Digital and E-commerce, Technology and more.

Overview

AI/ML Engineer III builds machine learning models, implements training and evaluation workflows, and supports integration of AI capabilities into production environments. In close collaboration with our Data Scientists, Data Engineers, and MLOps Engineers this role will scale machine learning algorithms, agentic solutions, and develop novel approaches to enterprise ai. This position plays a pivotal role in a fast-growing, globally focused network of data scientists, machine learning engineers, and AI practitioners, working to improve enterprise AI efficiency gains and agentic workflows. Our flexible/hybrid work schedule includes 3 in-person days at one of our core locations and 2 remote days. Our core office location for this role is Quincy, MA. Applicants must be currently authorized to work in the United States on a full-time basis.

Responsibilities

• Explore, design, and implement Generative AI and Retrieval-Augmented Generation (RAG) approaches to support enterprise AI use cases.
• Design and develop agentic AI solutions, leveraging appropriate agent architectures, system design patterns, tools, and frameworks.
• Develop RAG pipelines, including document chunking, embeddings, indexing, retrieval strategies, and integration with large language models (LLMs).
• Design and develop AI-powered chatbots and conversational applications using LLMs, enterprise data, and retrieval-based techniques.
• Evaluate and prototype emerging Generative AI, agentic AI, and retrieval techniques to improve solution quality, scalability, and maintainability.
• Build model serving applications for serving using REST microservices. Identify constraints, strengths, and weaknesses of technology options for model serving
• Assist in developing automated ML training and monitoring pipelines.
• Collaborate with engineering and product partners to refine AI solution requirements.
• Works closely within a team environment to incorporate collaborative business plans utilizing both internal and external data partners. Keep up with latest trends in industry on machine learning and gen ai space to enhance model performance
• May be called upon to support critical escalations and must be available during urgent IT incidents as needed.

Requirements

• Explore, design, and implement Generative AI and Retrieval-Augmented Generation (RAG) approaches to support enterprise AI use cases.
• Design and develop agentic AI solutions, leveraging appropriate agent architectures, system design patterns, tools, and frameworks.
• Develop RAG pipelines, including document chunking, embeddings, indexing, retrieval strategies, and integration with large language models (LLMs).
• Design and develop AI-powered chatbots and conversational applications using LLMs, enterprise data, and retrieval-based techniques.
• Evaluate and prototype emerging Generative AI, agentic AI, and retrieval techniques to improve solution quality, scalability, and maintainability.
• Build model serving applications for serving using REST microservices. Identify constraints, strengths, and weaknesses of technology options for model serving
• Assist in developing automated ML training and monitoring pipelines.
• Collaborate with engineering and product partners to refine AI solution requirements.
• Works closely within a team environment to incorporate collaborative business plans utilizing both internal and external data partners. Keep up with latest trends in industry on machine learning and gen ai space to enhance model performance
• May be called upon to support critical escalations and must be available during urgent IT incidents as needed.

Qualifications

• Master's degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field required; equivalent advanced experience in applied data science may be considered.
• 5+ years of AI/ML engineering experience.
• Expert coding ability in Python
• Strong understanding of agentic AI system design patterns and hands‑on experience developing AI agents and agent‑based workflows.
• Strong software engineering fundamentals, including data structures, algorithms, object-oriented design, modular development, testing, and maintainable code.
• Strong experience with scikit-learn, PyTorch, TensorFlow, and Hugging Face libraries and frameworks.
• Hands‑on experience building Retrieval-Augmented Generation (RAG) solutions, including embeddings, document chunking, indexing, retrieval, and integration with LLMs.
• Experience developing LLM‑powered chatbots and conversational AI applications.
• Understanding of Generative AI and LLM application architecture, including retrieval, context management, and agentic workflows.
• Knowledge of API development best practices, model management, code versioning and agile methodologies
• Understanding of deep learning and generative AI fundamentals.
• Strong analytical and communication skills.

Preferred Qualifications

• Experience in deploying models on azure cloud.
• Experience with cloud ML platforms.
• Experience deploying models on very large data using Databricks, Kafka and Kubernetes
• Experience working on cloud infrastructure ( Azure Preferred)
• Experience training and serving models on GPU(s)

Salary Range: $125,040 - $187,560

Actual compensation offered to a candidate may vary based on their unique qualifications and experience, internal equity, and market conditions. Final compensation decisions will be made in accordance with company policies and applicable laws.