Senior AI Consultant
- Londyn
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Project overview
Position overview
As part of our AI & ML team, you’ll lead and contribute to AI strategy and implementation initiatives — from roadmap design and maturity assessments to co-building pilots and reusable solution patterns. You’ll work across industries and functions, applying GenAI, data science, and modern cloud-native architectures to solve complex, high-impact challenges. This role blends strategic thinking with hands-on execution, and offers the opportunity to shape how AI is delivered at scale.
Responsibilities
- Lead AI strategy engagements from opportunity discovery through roadmap development, aligning AI adoption with client business goals, tech stack, and operating model
- Shape reusable solution architectures using modular components, copilots, and delivery accelerators from the Connect AI framework to ensure scalable, cross-client value
- Translate complex AI capabilities into business impact, working closely with CxO-level stakeholders to prioritize initiatives and quantify ROI
- Design and facilitate client workshops to align on goals, surface high-impact use cases, and assess AI maturity across technical, organizational, and data dimensions
- Contribute to DataArt’s evolving AI offerings, including vertical accelerators, governance models, and productized services with pricing and go-to-market relevance
Requirements
- 3–5+ years in AI, digital transformation, or strategy consulting, ideally in client-facing roles within tech-driven or innovation-led engagements
- Proven ability to define enterprise AI strategies and roadmaps, including maturity assessments, capability planning, and use case prioritization
- Strong business and technical fluency, with the ability to bridge AI/ML concepts and modern architectures with measurable executive-level business value
- Experience designing reusable toolkits, delivery frameworks, or productized services — ideally contributing to IP-backed consulting models
- Familiarity with GenAI ecosystems (e.g., LLMs, RAG, prompt engineering, agents) and their application across industry verticals and business functions
- Solid understanding of technical principles and architecture of ML/LLM applications and AI agents
- Hands-on experience with major cloud platforms (e.g., AWS, GCP, Azure) and their AI/ML service offerings
- Strong communication skills and effective stakeholder management
- Master’s degree in Computer Science, AI, Machine Learning, or a related field
Nice to have
- Exposure to AI monetization models, including usage-based pricing, enablement fees, or outcome-driven commercial constructs
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