Hybrid AI Engineer — Equity Stake & Rapid Impact

Shopping Excellence Corp; Rapid City (SD); Hybrid; USD 64,000 - 98,000; Full time

Benefits offered by this job

Full benefits

Hybrid schedule

Growth runway

Job summary

Shopping Excellence Corp's technology team seeks an AI Engineer to translate playful-technical outages into stable fixes and scalable pipelines in Rapid City, SD. The role offers a hybrid schedule and a mid-level stake in the company's direction, with a salary range of $64,000 to $98,000 and full benefits.

You'll help scale ETL pipelines, monitor model deployments, reduce technical debt, and build internal tooling that improves developer productivity, while keeping production incidents under

Qualifications

• 3+ years of experience and strong instincts.
• Ability to build rapport and communicate effectively with stakeholders.
• Empathy and constructive feedback skills.
• Comfort presenting ideas to stakeholders at all levels.
• Ability to steer technology discussions toward decisions.

Responsibilities

• Translate outages into fixes to stabilize launches.
• Scale ETL Pipelines services from pilot to statewide rollout.
• Monitor model deployment budgets and prevent overruns.
• Rewrite generative AI client-focused components to reduce technical debt.
• Build internal tooling to boost developer productivity and velocity.
• Keep Python CI under ten minutes for Rapid City engineers.
• Troubleshoot production incidents across Facilitation-based apps.
• Automate Plotly tasks to save engineering hours.

Skills

3+ years experience

rapport building

empathy

stakeholder presentation

decision facilitation

integrity

positive presence

Job description

Shopping Excellence Corp's technology team seeks an AI Engineer to translate playful-technical outages into stable fixes and scalable pipelines in Rapid City, SD. The role offers a hybrid schedule and a mid-level stake in the company's direction, with a salary range of $64,000 to $98,000 and full benefits.

You'll help scale ETL pipelines, monitor model deployments, reduce technical debt, and build internal tooling that improves developer productivity, while keeping production incidents under