Bank OZK is looking to solve the business and technical problem of implementing and monitoring scalable, production-grade Gen AI foundational/large language models (LLM) and agentic AI solutions to drive measurable business outcomes and achieve knowledge base parity with the industry.
Requirements
- Comprehensive knowledge of model fine-tuning and optimization techniques.
- Comprehensive knowledge of distributed systems and microservices architecture beyond AI applications.
- Comprehensive knowledge of machine learning fundamentals.
- Proficient skill with agentic AI orchestration tools such as LangGraph, AutoGen, and Camunda.
- Proficient skill in Python and Java for AI application development.
- Advanced skills in LLMs, NLP, and GenAI applications.
- Skill with cloud platforms (e.g. AWS, Azure, GCP) and containerization technologies (e.g. Docker, Kubernetes).
- Skill with databases including SQL, NoSQL, and vector databases.
- Ability to build scalable microservices and RAG systems.
Responsibilities
- Architects, designs and deploys LLM-based and agentic AI systems at scale, leveraging technologies such as GPT-4/5, LLaMA, Mistral, and Gemini.
- Develops and maintains retrieval-augmented generation (RAG) pipelines and agentic workflows using tools like LangGraph, AutoGen, Milvus, Pinecone, or Weaviate.
- Builds cloud-native, scalable microservices to support AI applications in production environments.
- Implements AI-powered applications using Python and Java, ensuring robust and maintainable codebases.
- Supports data ingestion, preprocessing, and prompt tuning to enable effective model development.
- Implements leadership strategy to deploy, monitor, version, and scale AI systems on cloud platforms.
- Enables and advocates the enterprise AI strategy, ensuring alignment with business objectives, regulatory requirements, and ethical standards.
Other
- Manages a multi-disciplinary team and fosters innovation across the enterprise.
- Drives the knowledge base parity & proof-of-concept development between Bank OZK and the industry.
- Collaborates with senior engineers, product managers, and research scientists to deliver enterprise-grade AI solutions.
- Ensures compliance, security, and responsible use of AI technologies across all deployed solutions.
- Monitors advancements in AI/ML research and tools to inform ongoing development and strategic direction.
- Strong problem-solving skills and ability to translate business challenges into technical solutions.
- Effective collaboration and communication skills across cross-functional teams.
- Strong organizational, critical thinking, and time management skills.
- Ability to maintain confidentiality and exercise discretion and sound judgment in technical decision-making.
- Ability to work minimal or no supervision.
- Ability to manage multiple projects or assignments and demonstrate flexibility in a continually changing environment.
