Senior AI Management Consultant, AI Natives

About the role

NCS's AI Central (AIC) builds, productises and deploys AI capabilities and reusable assets across regulated and mission-critical sectors. It is looking for an analytical, forward-thinking Senior AI Management Consultant to help clients find where AI creates business value and turn those opportunities into measurable outcomes. This is not a traditional advisory role: AI-native consultants combine structured problem solving and business acumen with a builder mindset, using AI across research, analysis, solution design and prototyping.

Key responsibilities

• Assess client AI readiness, data maturity, business processes and operational challenges, then develop AI strategies, business cases, transformation roadmaps and implementation plans.
• Redesign processes and operating models to embed AI, and define KPIs to track impact and adoption.
• Turn ambiguous challenges into solution hypotheses and work with engineering, data science and product teams to build prototypes, MVPs and deployable solutions.
• Run rapid experiments to validate value while balancing enterprise needs for security, reliability and governance.
• Lead client engagements independently, run workshops with stakeholders including C-suite executives, and advise on investment priorities and build-versus-buy-versus-partner decisions.
• Contribute reusable frameworks, methodologies and solution patterns that help scale NCS's AI capabilities.

Required profile

• 2-6 years of experience in management/strategy consulting, AI consulting, forward-deployed engineering, digital transformation or related fields.
• Experience in AI strategy, process transformation, operational excellence or digital transformation.
• Ability to manage multiple stakeholders and lead engagements independently.
• Strong analytical, strategic, commercial and structured problem-solving skills.
• Strong interest in AI with demonstrated ability to use AI tools effectively.

Required skills

• Experience taking AI ideas beyond strategy into prototypes, pilots or implementation.
• Hands-on exposure to Python, analytics, automation, AI development or low-code/no-code tools.
• Understanding of GenAI, LLMs, AI agents and automation technologies.
• Experience with engineering, data science or product teams, and in regulated or complex enterprise environments.