- Company Name
- Cleverfox AI
- Job Title
- Senior AI Solution Consultant
- Job Description
-
Job title: Senior AI Solution Consultant
Role Summary: Lead client‑facing AI strategy and technical delivery, translating business challenges into AI solutions. Work at the intersection of consulting, business analysis, and technical leadership to design scalable architectures and drive commercial outcomes.
Expectations:
- Own end‑to‑end engagement from discovery to production and adoption.
- Shape product offerings, frameworks, and delivery standards for a growing AI consultancy.
- Provide entrepreneurial, commercially‑aware leadership while managing technical risk and quality.
- Mentor and influence a small, founding‑level team; contribute to practice building and IP creation.
Key Responsibilities:
- Conduct discovery workshops, stakeholder interviews, and business analysis to identify AI opportunities and define success metrics.
- Translate requirements into clear roadmap documents, solution options, and ROI justifications.
- Design, prototype, and lead implementation of AI solutions, including LLM integration, vector databases, agent orchestration, and workflow automation.
- Build reusable reference architectures, data pipelines, and governance standards for scalable, secure deployments.
- Ensure cloud‑based deployment (AWS, Azure, GCP) and MLOps best practices.
- Deliver presentations to senior stakeholders, challenge assumptions, and advocate for high‑impact initiatives.
- Identify upsell and cross‑sell opportunities, supporting business development.
- Mentor junior staff, support hiring, and contribute to internal playbooks and case studies.
Required Skills:
- Proven experience in client‑facing consulting (digital transformation, AI/ML, product discovery).
- Strong technical background: Python, PyTorch / Hugging Face, scikit‑learn, R or equivalent.
- Practical experience with large language models, prompt engineering, vector databases (e.g., Pinecone, Milvus), and agent frameworks (e.g., LangChain, RPA tools).
- Familiarity with MLOps, CI/CD pipelines, and cloud deployment (AWS, Azure, GCP).
- Ability to produce structured documentation, presentations, and evidence‑based ROI models.
- Entrepreneurial mindset, commercial acumen, and comfort with ambiguity and rapid iteration.
- Excellent communication skills, able to explain technical concepts to non‑technical stakeholders.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate) are a plus but not mandatory.