Trust Architect - Responsible AI, Risk & Governance

Trust Architects build trust in the AI and trust among the people who use it. They make sure every system Avanade Next ships is safe, reliable and ready for production — and that the client's people are confident, capable and willing to adopt new ways of working alongside it.

The role operates across two dimensions. Trust in the AI: evaluation frameworks, accuracy measures, security controls, governance controls and human-in-the-loop safeguards. Trust in the people: adoption design, capability uplift, ways of working and confidence in human-agent collaboration.

Governance & Guardrails

• Set governance, risk and security guardrails before build begins.

• Embed controls, human review and feedback loops as the system evolves.

• Support regulatory and privacy positions with the right client and Avanade specialists.

Evaluation & Release Assurance

• Design and run evaluations, including accuracy targets, test harnesses and release evidence.

• Hold the release gate with delivery and quality teams.

• Work shoulder to shoulder with FDEs so trust and monitoring are built in.

Adoption & Ways of Working

• Design adoption and change approaches that build confidence through transparency, education and demonstrated outcomes.

• Help clients redesign human-agent interaction so systems fit real work.

• Track active usage and effective human oversight after go-live.

Contribution & Reuse

• Support executive and Board confidence with clear governance and accountability frameworks.

• Contribute evaluation harnesses, guardrail patterns, governance frameworks and adoption assets.

• Provide independent challenge where trust risks are not being addressed.

• Governance, guardrails and security controls in place before build starts.

• Target accuracy, safety and governance thresholds met before production.

• Adoption above agreed threshold at 90 days post-go-live.

• Compliance with responsible AI standards and client obligations.

• Reusable trust, evaluation and adoption assets contributed from every engagement.

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• 5+ years across AI governance, model risk, security, responsible AI, or large-scale technology change and adoption. Strength in two of these with a credible path into the third is expected — few candidates will have all of it.

• Hands-on evaluation experience with generative or agentic systems is strongly preferred over policy-only backgrounds.

• Working knowledge of the APAC regulatory environment relevant to their market.

• Practical change and enablement capability with technical audiences and frontline users alike.

• Able to build trust with sceptical stakeholders and to say no with evidence.

• Comfortable in a role that is still being defined, in a track with no established internal precedent.

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