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Senior, niche GenAI leadership role with hands-on requirements reduces candidate pool despite metro location.
Requires specialized ML/GenAI and transformation experience but skills remain transferable across industries.
Explicit 8–12 years, mandatory AI delivery experience, technical and governance requirements make screening stringent.
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Identify and define AI use cases to improve business workflows, productivity, quality, and client experience with measurable outcomes.
Design AI solution architectures considering integration, data flow, model selection, controls, and operational ownership across multi-stack AI platforms.
Lead hands-on development and delivery of AI prototypes and MVPs; manage AI initiatives from discovery to implementation handoff ensuring milestones, risks, and stakeholder alignment.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Statistics, Mathematics, or related quantitative/technical discipline.
8–12 years of professional experience in AI solution engineering, digital transformation, solution architecture, consulting, or intelligent automation.
At least 3 years experience delivering AI, analytics, automation or data-driven digital solutions addressing business workflow problems.
Prefers certifications such as Microsoft Azure AI Engineer, Google Cloud AI/ML, or recognized GenAI/responsible AI credentials.
Experienced in AI and GenAI technologies including LLMs, prompt engineering, RAG, and AI risk evaluation with hands-on Python and low-code automation development.
Skilled in translating business needs into practical AI integrations involving cloud AI services, APIs, security, and data pipelines with a governance and responsible AI mindset.
Proven track record in consulting-style problem framing, stakeholder engagement, delivery leadership with scope, risk management, and adoption planning in financial services, consulting, or GCC environments.