The Role
Convert SME outputs into production-ready agent knowledge (Agent DNA), resolve conflicting inputs, ensure traceability and evidence quality, and establish repeatable knowledge-ops workflows with Product, Design, and Engineering to enable certification readiness for reference agents.
Summary Generated by Built In
We are looking for a professional responsible for the final stage between expert input and the agent's 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.
Skills Required
- 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.
- Ability to use AI to cluster, normalize, draft, compare, and summarize SME inputs while maintaining human traceability.
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The Company
What We Do
The company provides automation and process optimization, UX innovation, software designing and testing, big data, artificial intelligence, and machine learning. They are involved in the development of computer systems and IT consulting.
