AI Solutions Architect - Python
Title: AI Solutions Architect - Python Location: New York, NY
Duration: 6 Months Contract. Interview Mode : Phone + Video Job Description:
We are seeking an experienced Temporary Manager – Risk Technology to support AI, automation, analytics, and technology transformation initiatives within a Credit Review and risk-focused environment. This role will focus on enhancing and scaling existing AI and automation solutions, developing data and document-processing capabilities, and expanding technology-enabled workflows across lending portfolios and business use cases.
Required Qualifications:
Strong hands-on experience developing applications, automation solutions, or data-processing workflows using Python.
Experience building or implementing solutions utilizing AI, machine learning, generative AI, or large language models.
Experience working with OpenAI APIs or similar LLM technologies and integrating them into business applications or workflows.
Experience designing solutions that process both structured and unstructured data, including documents and large datasets.
Demonstrated experience developing and deploying scalable AI or automation solutions within a regulated environment.
Ability to translate business requirements into practical and scalable technical solutions.
Strong communication and stakeholder management skills with the ability to work across technical and business teams.
Ability to operate at a Manager level, balancing hands-on technical execution with solution ownership and stakeholder engagement.
Preferred Qualifications:
Experience developing Alteryx workflows and ETL processes.
Experience with Power BI, dashboard modernization, or reporting automation.
Familiarity with financial services, credit risk, credit review, risk management, internal audit, or related environments.
Experience supporting technology transformation or automation initiatives within a financial institution or other highly regulated organization.
Ideal Candidate Profile:
A strong candidate will be someone who can bridge risk and technology. They should be comfortable getting hands-on with Python, AI/LLM integrations, data, and automation while also working directly with business stakeholders to understand risk processes and determine where technology can improve efficiency, scalability, and consistency.