Senior AI Engineer

Jack Henry & Associates is hiring a Senior AI Engineer for a hybrid role based in Springfield, MO (at least 1 day per week in an approved office location). This position focuses on bridging AI experimentation with production engineering so AI systems can be delivered as reliable, secure, enterprise-ready solutions
, with attention to compliance and governance
. You will collaborate across engineering, quality, security, and architecture to operationalize AI capabilities at scale.

• Lead and perform system analysis and programming to move AI proofs of concept into production-ready software
  , including research when no established pattern exists.
• Provide engineering support for applications across the lifecycle, from code delivery through application retirement
  .
• Develop, test, and review applications aligned to business requirements and industry best practices.
• Use best practices, standard guidance, and agentic development workflows to create and modify code.
• Consider impacts of code changes on end users and internal teams
  , and review work produced by less experienced engineers.
• Partner with quality and security stakeholders (including cybersecurity
  , cloud infrastructure
  , and AI governance
  ) to support timely delivery of high-quality products.
• Work independently on critical tasks by setting and updating expectations for scope
  , timelines
  , and delivery size
  .
• Create required technical documentation
  , and participate in cross-functional discussions and meetings.
• Stay current on emerging AI technologies and industry trends, recommending improvements to software development processes.
• Adhere to departmental and corporate standards, and help define what production-ready means for AI systems at Jack Henry.

• Lead unit tests
  , integration tests
  , and evals to improve reliability, security, and performance of developed software, especially AI systems and workflows.
• Debug and troubleshoot issues as they arise, including AI-specific failure modes such as quality drift
  , prompt regressions
  , provider outages
  , and cost spikes
  .
• Contribute to product architecture when needed.
• Build and support production AI capabilities, including AI Gateway services
  , MCP integrations
  , agent frameworks
  , self-hosted inference
  , and AI-powered applications
  .
• Develop and improve testing, evaluation, monitoring, logging, and observability practices so AI systems remain dependable
  , scalable
  , and auditable in production.
• Improve AI system performance using model evaluation, operational monitoring, quality assurance, and continuous improvement.
• Mentor engineers, establish AI development best practices, and drive adoption of AI technologies and agentic workflows across the organization.

• 6+ years of technical experience in software development.
• Production ownership of AI systems (AI agents, AI features in products, MCP servers, etc.).
• Experience with a major cloud environment:
  GCP
  , AWS
  , or Azure
  .
• Experience with unit testing and end-to-end automated testing
  .
• Experience with Kubernetes
  .
• Experience with at least one:
  Large language models (LLM),
  vector databases
  .
• Comfort with ambiguity and shifting priorities.
• Self-directed style with willingness to push through roadblocks.
• Travel up to 10% to attend internal business meetings, training, and/or professional conferences.

• GCP, AWS, Azure
• Kubernetes
• Large language models (LLM), vector databases
• AI Gateway services, MCP integrations, agent frameworks
• Self-hosted inference
• Unit testing, end-to-end automated testing
• Observability

Outstanding benefit programs to ensure the physical, mental, and financial well-being of people is always met.

This position is hybrid and requires at least 1 day per week in any of the following office locations:

• Allen, TX
• Louisville, KY
• Birmingham, AL
• Cedar Falls, IA
• Charlotte, NC
• Overland Park, KS
• Monett, MO
• Springfield, MO

This position is ineligible for immigration sponsorship and support
.

• Bachelor’s degree.
• Fintech experience.
• Experience with GCP and infrastructure as code (Terraform).
• Experience in cloud security and Dev Ops.
• Experience with model fine-tuning, evaluation (including controlling for bias), and validation.
• Experience with AI observability, evals, and model monitoring.