Senior Software Engineer – Generative AI Innovation

Overview Client•Overland Park, KS

About The Position

Client is seeking a Senior Software Engineer – Generative AI Innovation to serve as a hands-on technical leader focused on identifying, evaluating, prototyping, and delivering Generative AI solutions that create business value. This role combines software engineering, applied AI research, solution prototyping, and emerging technology evaluation to accelerate AI adoption across Institutional Banking. The successful candidate will collaborate with business stakeholders, technology partners, and governance teams to transform ideas into working solutions, guide initiatives through governance processes, and support the transition of validated solutions into production environments. This role requires strong technical curiosity, initiative, and the ability to operate independently while advising on emerging AI technologies and industry developments.

Requirements

5+ years of professional software engineering experience developing web-based or distributed applications.
Demonstrated experience building software solutions using modern programming languages, frameworks, APIs, and cloud services.
Hands-on experience working with Generative AI technologies, large language models (LLMs), AI-enabled applications, or related emerging technologies.
Strong problem-solving skills with the ability to independently navigate ambiguity and rapidly learn new technologies.
Excellent written and verbal communication skills with the ability to explain technical concepts to non-technical audiences.
Proven ability to take ownership of complex problems and drive solutions from concept through implementation.
Bachelor's degree or equivalent experience preferred.

Nice To Haves

Experience with cloud platforms such as Google Cloud Platform (GCP) and/or Microsoft Azure.
Experience implementing or evaluating Retrieval Augmented Generation (RAG), agentic AI workflows, document intelligence solutions, or workflow automation platforms.
Experience operating within regulated industries and partnering with governance, risk, compliance, security, or legal functions.
Experience evaluating vendor technologies and making technical recommendations to business and technology leadership.
Experience supporting proof-of-concept development, experimentation, and innovation initiatives.

Responsibilities

Design, build, and deploy proof-of-concept and production-ready Generative AI solutions using modern software engineering practices and cloud-native technologies.
Evaluate, prototype, and validate emerging Generative AI platforms, tools, vendors, and capabilities to determine applicability and value for business use cases.
Develop AI-enabled applications and workflows utilizing large language models (LLMs), Retrieval Augmented Generation (RAG), agentic AI frameworks, document intelligence technologies, workflow automation platforms, APIs, and cloud services.
Rapidly transform business ideas into working software solutions through technical experimentation, prototyping, and solution validation.
Partner with business stakeholders to identify opportunities where AI can improve productivity, decision-making, client service, operational efficiency, and risk management.
Provide technical input, documentation, and support for governance, risk, compliance, model review, and technology approval activities related to AI initiatives.
Research industry trends, emerging technologies, and vendor capabilities, and communicate recommendations to technology and business leadership.
Design and implement integrations between AI platforms, enterprise systems, and cloud services.
Establish engineering standards, reusable patterns, and best practices for AI solution development.
Develop secure, maintainable, testable, and high-quality code while supporting production deployments, troubleshooting, and continuous improvement efforts.
Create technical documentation, reference architectures, implementation guidance, presentations, and demonstration materials.
Present prototypes, findings, recommendations, and solution roadmaps to stakeholders and senior management.
Maintain awareness of evolving AI regulatory, governance, security, and risk management considerations and incorporate appropriate controls into solution designs.