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Agent Editor Knowledge Engineer 1753

SOFTGIC

Job Location:

Medellín - Colombia

Monthly Salary: COP 2000 - 2000

Experience Required: 1-3years

Posted: 24 June 2026 (30+ days ago)

Application Deadline: 21 September 2026

Vacancies: 1 Vacancy

Job Summary

We are looking for a professional responsible for the final stage between expert input and the agents DNA ready for launch. This role synthesizes structured expert information resolves ambiguities and prepares knowledge resources ready for publication.

Key Responsibilities

Translate SME exercise output into clean Agent DNA fragments and supporting artifacts.

Reconcile conflicting SME input and surface unresolved ambiguities for product or architecture decisions.

Maintain evidence-map quality policy clarity and traceability back to source input.

Partner with Product Design and Engineering on certification readiness for the first reference agent.

Establish repeatable knowledge-ops working practices for future SME pods.

Requisitos

Must-Have Qualifications

Strong analytical writing and systems-thinking ability.

Experience turning ambiguous expert input into structured requirements rules or knowledge assets.

Comfort working with technical teams and non-technical domain experts.

Excellent judgment around precision traceability and ambiguity handling.

AI-First Expectations

Uses AI to cluster normalize draft compare and summarize SME inputs at speed.

Never treats AI-generated synthesis as final truth; human traceability and certification readiness are the quality bar. What Success Looks Like in the First 90 Days

The first SME exercise outputs are translated into release-ready DNA fragments.

A repeatable knowledge-ingestion workflow exists.

Engineering is not acting as the default bottleneck for SME translation.

Required Skills:

Must-Have Qualifications Strong analytical writing and systems-thinking ability. Experience turning ambiguous expert input into structured requirements rules or knowledge assets. Comfort working with technical teams and non-technical domain experts. Excellent judgment around precision traceability and ambiguity handling. AI-First Expectations Uses AI to cluster normalize draft compare and summarize SME inputs at speed. Never treats AI-generated synthesis as final truth; human traceability and certification readiness are the quality bar. What Success Looks Like in the First 90 Days The first SME exercise outputs are translated into release-ready DNA fragments. A repeatable knowledge-ingestion workflow exists. Engineering is not acting as the default bottleneck for SME translation.

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