AVP Senior AI ML Engineer

Bank OZK•Dallas, TX

About The Position

Leads the development of scalable artificial intelligence systems, focusing on prompt tuning, retrieval-augmented generation (RAG) pipelines, and microservices architecture to advance Bank OZK’s enterprise AI initiatives. Collaborates across teams to deliver production-ready AI applications that drive innovation, operational efficiency, and enhanced customer experiences. The role designs and optimizes prompts for generative AI and agentic models and systems, develops RAG pipelines and agentic workflows, builds cloud-native microservices, and implements AI applications using Python and Java. It also supports data preparation and model deployment, monitoring, versioning, and scaling on cloud platforms. The position works with engineers, product managers, and research scientists and tracks developments in AI/ML research and tools.

Requirements

Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related field, or commensurate work experience.
At least 4 years of experience in AI/ML engineering or applied AI system development.
General knowledge of model fine-tuning and optimization techniques.
General knowledge of distributed systems and microservices architecture beyond AI applications.
General knowledge of machine learning fundamentals.
Strong problem-solving skills and ability to translate business challenges into technical solutions.
Effective collaboration and communication skills across cross-functional teams.
Proficient skill with agentic AI orchestration tools such as LangGraph, AutoGen, and Camunda.
Strong organizational, critical thinking, and time management skills.
Proficient skill in Python and Java for AI application development.
Strong skills in LLMs, NLP, and generative AI applications.
Skill with cloud platforms such as AWS, Azure, or GCP and containerization technologies such as Docker and Kubernetes.
Skill with SQL, NoSQL, and vector databases.
Ability to maintain confidentiality and exercise discretion and sound judgment in technical decision-making.
Ability to work under minimal supervision.
Ability to manage multiple projects or assignments and demonstrate flexibility in a continually changing environment.
Ability to build scalable microservices and RAG systems.
Ability to operate customary equipment and technology used in a business environment, with or without accommodation.

Responsibilities

Design and optimize prompts for generative AI and agentic models and systems, including large language models such as GPT, LLaMA, Mistral, and Gemini, to achieve business-focused outcomes.
Develop and maintain retrieval-augmented generation (RAG) pipelines and agentic workflows using tools such as LangGraph, AutoGen, Milvus, Pinecone, or Weaviate.
Build cloud-native, scalable microservices to support AI applications in production environments.
Implement AI-powered applications using Python and Java, maintaining robust and maintainable codebases.
Support data ingestion, preprocessing, and feature engineering for model training and deployment.
Assist with deployment, monitoring, versioning, and scaling of AI systems on cloud platforms.
Collaborate with senior engineers, product managers, and research scientists to deliver enterprise-grade AI solutions.
Monitor advancements in AI/ML research and tools to inform ongoing development and strategic direction.
Perform other duties as assigned.