Principal – AI Strategy, Automation Architect

Responsibilities

• Partner with AI strategy, analytics, advisory, and delivery teams to translate outcome‑led AI methods into scalable technical assets.
• Design and build practical tools that support AI opportunity mapping, KPI alignment, readiness assessment, value realization, health checks, journey analysis, and outcome measurement.
• Support complex customer and internal scenarios by assessing technical feasibility, data availability, integration considerations, and automation opportunities.
• Translate ambiguous strategic needs into working prototypes, data workflows, proof‑of‑concept applications, and reusable technical patterns.
• Help internal teams move from manual, one‑off analysis toward repeatable, scalable, and automated methods.
• Build internal accelerators, lightweight applications, scripts, dashboards, data workflows, and automation assets that improve team efficiency and consistency.
• Develop prototypes that demonstrate how AI strategy, measurement, and operational data can be connected to actionable recommendations.
• Create reusable automation patterns for customer health checks, KPI tree generation, value realization scorecards, readiness assessments, use case prioritization, and engagement preparation.

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Analytics, Mathematics, or a related technical field, or equivalent practical experience.
• 10+ years of experience in technical architecture, solutions engineering, data engineering, automation, analytics engineering, AI solutions, SaaS platforms, customer experience technology, or related fields.
• Strong hands‑on development experience with languages and tools such as Python, SQL, JavaScript, APIs, cloud services, automation platforms, BI tools, or related technologies.
• Experience building prototypes, internal tools, technical accelerators, dashboards, data workflows, scripts, or lightweight applications.
• Strong understanding of APIs, data integration, analytics data, automation patterns, and technical solution design.
• Ability to work with ambiguous business problems and convert them into practical technical approaches.
• Understanding of AI, automation, LLMs, analytics, data workflows, and customer experience technology.
• Ability to communicate technical concepts clearly to business, advisory, and executive audiences.
• Proven ability to partner across strategy, technical, advisory, and delivery teams.
• Strong judgment around when to prototype, when to automate, when to simplify, and when to recommend a more formal delivery path.