AI Automation Lead - Build, Test & Deploy Digital Workers

Kforce Inc

St. Louis (MO)

On-site

USD 90,000 - 140,000

Full time

2 days ago

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Job summary

Kforce has a client seeking an AI Automation Consultant in Saint Louis, MO. You will take solution designs from the Solutions Architect and bring them to life, building, testing, and deploying Digital Workers in Maisa Studio.

You own everything from first configuration through go-live and handover to operations. You will execute UAT with production data, certify that Digital Workers meet KPIs, and collaborate with the Solutions Architect to ensure the build matches the designed experience.

Qualifications

Bachelor's or Master's degree in IT, Engineering, or related field.
Hands-on automation development experience.
Experience with low-code/no-code platforms.
Experience with APIs and integrations in delivery contexts.
Fluent in Spanish and English.
Strong attention to detail.
Proven ability to learn new platforms quickly.

Responsibilities

Build and configure Digital Worker configurations in Maisa Studio based on technical specifications from the Solutions Architect.
Configure integrations including APIs, connectors, and data flows as defined in the solution design.
Raise specification gaps or feasibility issues early; don't wait, don't assume.
Own and execute UAT with production data, documenting results and resolving defects.
Certify that Digital Workers meet defined KPIs and success criteria before go-live.
Collaborate with the Solutions Architect during UAT to confirm the build matches the designed experience.
Manage go-live deployment following established procedures.
Hand over to operations with complete documentation: configuration details, known limitations, runbooks, and support notes.
Ensure operational teams have everything they need to maintain the Digital Worker post-launch.
Partner closely with the Solutions Architect; ask questions, challenge assumptions, flag risks early.
Provide effort estimates to support the Architect's scoping and delivery planning.
Share reusable configurations, shortcuts, and lessons learned with the broader engineering team.
Support fellow engineers when they hit blockers; team delivery matters more than individual output.