AI consultant

DataArt’s AI Lab helps organizations turn AI from experimentation into transformation — with practical, scalable solutions that drive real business outcomes. We combine strategic advisory, deep engineering, and reusable delivery accelerators through our Connect AI framework to enable smarter operations, faster decision-making, and sustainable growth.

• 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

• 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
• Exposure to AI monetization models, including usage-based pricing, enablement fees, or outcome-driven commercial constructs

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