Bring your research and consulting expertise into MetaBrain solution development. Turn industry knowledge and advisory methods into reusable, continuously updated software-enabled services.
MetaBrain combines Frost & Sullivan’s 65 years of industry expertise, enterprise data, and third-party insights, delivering human-reinforced AI insights and analytics to solve your toughest business use cases with actionable, real-time intelligence.
The work
Selected colleagues will build decision-intelligence models, knowledge structures, evaluation assets and governed workflows for Growth Pipeline Management (GPM) and other approved research/advisory use cases.
The ambition extends beyond generating reports or building a generic chatbot: create configurable solutions that help clients identify opportunities, evaluate alternatives, simulate scenarios and monitor change, with accountable advisor review.
Key responsibilities
Reporting to Chief Architect - Business, and with technical accountability to Chief Architect - Technology, the incumbent will be responsible to turn Frost research and advisory methodologies into configurable MetaBrain decision-intelligence solutions. Lead the translation from a client decision to its data, logic, workflow, user experience and acceptance criteria, working with a qualified technology counterpart.
- Define the decision and product. Run discovery with advisors and clients; define the decision owner, alternatives, constraints and measurable value. Prioritize reusable Growth Pipeline Management (GPM) modules rather than one-off report automation.
- Codify the advisory method. Map inputs, process and outputs; create taxonomies, concept relationships, scoring rules, scenario assumptions and evidence requirements. Separate measured facts, expert judgment, forecasts and unresolved gaps.
- Lead the build and validation. Translate the method into specifications and a delivery backlog. Configure advisor Design/Tuning and client Advisory/Simulation experiences with the team; coordinate pilots, advisor review, change control and adoption.
- Design for repeatability. Define configuration boundaries, update frequency, operating costs and reusable components. In the technology variant, additionally own approved API, orchestration, identity, reliability and deployment designs, supported by engineering review.
Essential requirements
- A strong record of leading research or consulting engagements and explaining industry economics; typically 6+ years of relevant experience, with equivalent achievement considered.
- Demonstrated client discovery, framework design, quantitative interpretation and cross-functional leadership. Foundational AI learning through a certificate, assessed course or equivalent, plus a practical example of AI-assisted research with source checking.
- Preferred: Product management, solution design, workflow automation, industry knowledge modelling, business analytics or enterprise-platform exposure. An MBA or relevant postgraduate qualification is useful, not mandatory.
- Entry level and authority: Business-led entry does not require production coding. Appointment as Lead Architect - Technology requires separate evidence of software architecture, integrations, secure deployment and technical delivery; an AI certificate alone is insufficient.