Accenture AI Engineer Case Interview: Client-Ready GenAI/ML Solution Design and Delivery

This case mirrors Accenture’s client-facing, consulting-led AI engineering interviews. You’ll be given a brief from a Fortune 500 client (e.g., modernizing customer operations with a GenAI assistant across channels) and asked to structure the problem, propose an end-to-end solution, and articulate delivery and value—using clear, hypothesis-driven communication. Focus areas reflect Accenture’s culture of ecosystem-led, responsible, and scalable delivery: 1) Problem framing and success metrics: translate business goals into measurable outcomes (e.g., CSAT +2–3 pts, cost-to-serve −15%, SLA adherence) and define model/product KPIs (latency, accuracy, safety). 2) Data and governance: outline data sources, privacy/sovereignty (GDPR/CCPA), security, lineage, and access patterns; propose a lightweight data contract and feature/embedding strategy. 3) Architecture on cloud: present a cloud-agnostic reference (Azure/AWS/GCP) covering ingestion, storage, model serving, vector/feature stores, APIs, and integration with enterprise apps (ServiceNow, Salesforce, contact center, knowledge bases). 4) Model strategy: compare classical ML vs. LLM/GenAI, fine-tuning vs. retrieval-augmented generation, evaluation plans, guardrails, prompt management, hallucination mitigation, bias/fairness—aligned to Accenture Responsible AI practices. 5) MLOps/ModelOps: CI/CD for models and prompts, data/versioning, automated testing, canary/AB rollouts, monitoring (quality, drift, safety), rollback, and SLA design for a managed run state. 6) Delivery and ways of working: propose an Agile plan with phases (discovery/Pilot/MVP/Scale), roles across Accenture’s global delivery network, change management and training (Talent & Organization), and a transition-to-managed-services approach. 7) Commercials and value: high-level TCO, licensing/infra estimates, build-vs-buy tradeoffs using partner accelerators (e.g., AIP+ where applicable), and a benefits realization plan with executive-ready storytelling. The assessor will probe on consulting behaviors (structured, MECE, client empathy), collaboration, and the ability to tailor the solution to industry context while leveraging Accenture’s ecosystem partnerships and repeatable accelerators.