Senior AI/ML Engineer (LLM)
Confidential
Posted: March 23, 2026
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Quick Summary
Develop and deploy leading-edge AI/ML models that power our financial institutions' innovative lending and banking systems. Collaborate with cross-functional teams to deliver high-quality solutions that drive business growth. Contribute to shaping the future of financial technology.
Required Skills
Job Description
About iBusiness
iBusiness is a leading financial technology company transforming the way banks, credit unions, and lenders innovate. As a pioneer in secure AI, automation, and AI software development, iBusiness builds infrastructure and platforms that empower financial institutions to modernize faster—without sacrificing compliance or security. Its technology enables seamless digital transformation across lending, banking, and customer experience systems, giving institutions the tools to compete and innovate at enterprise scale.
Join us and be part of a team that’s transforming the finance industry and empowering businesses to thrive!
Position Description
We are seeking an experienced Senior LLM Engineer to join our team. You will play a key role in designing and implementing workflows that leverage large language models (LLMs, LAMs, LMMs, LVLMs, etc.) to automate the process and drive innovation in our products. The ideal candidate will have a deep understanding of NLP, experience with foundational models, and a flexible, problem-solving mindset. You will collaborate closely with cross-functional teams, contributing to the development of scalable AI-driven solutions.
Major Areas of Responsibility
Design, implement, and optimize document intelligence pipelines that leverage LLMs to extract, interpret, and structure information from unstructured and semi-structured documents (PDFs, images, forms, contracts, etc.)
Leverage existing foundational models and adapt them to fit into various product requirements, ensuring alignment with business goals.
Collaborate with product managers, data scientists, and software engineers to integrate LLM-based automation into scalable solutions.
Create and architect Interpreters, Agented Systems
Architect and implement document-centric RAG systems, enabling accurate retrieval and reasoning over large corpora of documents
Develop systems for key-value extraction, table extraction, and entity recognition from complex documents (e.g., invoices, financial statements, contracts)
Research and evaluate new technologies and methodologies in the LLM space to continuously improve product automation.
Work on the customization and fine-tuning of models to optimize performance for specific use cases.
Develop, test, and deploy LLM-based services in production environments.
Provide technical leadership and mentorship to other engineers on the team.
Ensure that LLM integrations are efficient, scalable, and secure, adhering to industry best practices.
Required Knowledge, Skills, and Abilities
5+ years of experience with document processing systems, including OCR and text extraction tools (e.g., Tesseract, AWS Textract, Azure Form Recognizer, Google Document AI)
Experience working with unstructured and semi-structured data (PDFs, scanned images, forms)
Proven experience working with foundational models in production environments.
Strong programming skills in Python with experience in relevant ML libraries.
Hands-on experience in deploying machine learning models at scale.
Excellent communication and collaboration skills, with the ability to work cross-functionally.
Problem-solving mindset, with the flexibility to adapt models and workflows to evolving product needs.
Nice To Haves
Master’s or PhD in Computer Science, AI, Machine Learning, Physics or a related field.
Experience with MLOps and AWS
Familiarity with reinforcement learning and other advanced NL techniques.
Experience building risk modules
The anticipated salary range for this position is $170,000 - $210,000 annually, depending on experience and qualifications. iBusiness Funding provides a comprehensive benefits package, including medical, dental, and vision coverage; 401(k) with company match, and paid time off.
Conclusion:
This job description is intended to convey information essential to understanding the scope of the job and the general nature and level of work performed by job holders within this job. This job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities, or working conditions associated with the position.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, genetic information, or any other characteristic protected by law.