Job Title- AI Engineer

Location- St. Louis, MO

Knowledge:

Deep understanding of the full PDLC, from ideation and requirements through design, development, testing, security, deployment, and operations, including where AI can meaningfully augment each stage.
Strong working knowledge of modern AI tooling, particularly generative AI assistants, automation frameworks, developer assistances (e.g. GHCP, Claude Code), and current / emerging best practices, with the ability to evaluate and adopt tools pragmatically rather than by vendor alignment.
Solid grounding in responsible AI, including data privacy, security, model risk management, and ethical principles, with experience embedding governance and compliance controls directly into delivery workflows.
Familiarity with defining and tracking metrics to measure AI impact on engineering and product outcomes, such as cycle time, defect rates, test coverage, and operational stability.

Skills

Ability to embed directly with teams and coach through hands-on application, working shoulder-to-shoulder with engineers, product managers, and QA to apply AI in real scenarios.
Ability to define and operationalize AI standards, patterns, and best practices, including usage guidelines, prompt conventions, reference architectures, and reusable templates.
Proven capability to design and deliver enablement programs, including playbooks, training materials, workshops, and hands-on coaching that translate AI concepts into practical day-to-day application.
Technical proficiency in integrating AI solutions into existing toolchains, such as IDEs, CI/CD pipelines, testing frameworks, and monitoring platforms, including rapid prototyping to demonstrate value.

Strong communication and change leadership skills, with the ability to influence executives and earn credibility with engineering and product teams, addressing concerns and driving adoption