- Company Name
- Version 1
- Job Title
- AI Innovation Consultant
- Job Description
-
**Job Title:** AI Innovation Consultant
**Role Summary:** Drives AI adoption for enterprise customers by converting high‑level ambitions into rapid prototypes, proofs‑of‑concept, and scalable solutions, ensuring business value, ethical compliance, and stakeholder alignment.
**Expectations:**
- Deliver end‑to‑end AI engagements, from discovery to measurable ROI.
- Exhibit strong business analysis, product thinking, and AI expertise.
- Communicate complex concepts clearly to non‑technical audiences.
- Mentor junior teammates and contribute reusable practice assets.
**Key Responsibilities:**
- Lead workshops (problem framing, ideation, prioritisation) with clients and cross‑functional teams.
- Convert insights into testable hypotheses and experiment slices.
- Own multi‑stakeholder engagements and steer rapid prototypes or POCs.
- Translate business problems into scoped AI use cases, write user stories, define MVP scope and learning plans.
- Run lightweight experiments to validate assumptions early.
- Assess data readiness, recommend AI patterns (prompting, RAG, agent orchestration).
- Shape high‑level POC architecture with constraints, guardrails, quality, cost, and risk metrics.
- Collaborate with data science/engineering to design feasible, deployable solutions.
- Build business cases and ROI models; present findings to senior stakeholders.
- Define KPIs, track outcomes, recommend continuous improvements.
- Identify high‑risk AI uses, recommend policy and technical safety controls aligned with AI Act and client rules.
- Produce decision logs, runbooks, demo scripts for delivery teams.
- Coach associates on co‑creation, safe AI use, and company values.
- Contribute reusable IP, sales collateral, and best‑practice templates.
**Required Skills:**
- Consulting or business‑analysis experience with project coordination.
- Strong problem‑solving, analytical reasoning, and data‑driven mindset.
- Hands‑on familiarity with AI/ML concepts; experience experimenting with AI tools.
- Proficiency in creating presentations, business cases, and strategic documents.
- Excellent written and verbal communication; ability to explain technical concepts to non‑technical stakeholders.
- Workshop facilitation skills (or willingness to develop).
- Ability to coordinate across data, engineering, and business teams.
**Additional Desirable Skills & Experience:**
- Proven ability to create rapid POCs or prototypes using low‑code, Miro, Figma, Lovable, Google AI Studio, etc.
- Familiarity with Azure, AWS, or GCP cloud platforms and AI frameworks.
- Exposure to Agile delivery, backlog management, and backlog refinement.
- Experience in regulated sectors such as financial services or government.
- Current AI/ML certifications or active learning (bootcamps, online courses, self‑study).
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Science, Business Analysis, Engineering, or related field.
- Certifications:
- AI/ML professional certification (e.g., Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, Google Cloud Professional Data Engineer).
- Product Management or Agile Scrum certifications (e.g., Certified Scrum Product Owner, Professional Scrum Master).