About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
Position Overview
We are seeking an experienced Business Consultant with exceptional business analysis and consulting skills to drive the successful adoption of Agentic AI solutions within our corporate banking client organizations. This strategic role bridges the gap between cutting-edge AI capabilities and practical banking business outcomes. You will serve as the critical link between client stakeholders, technical teams, and program leadership, ensuring that AI solutions deliver measurable business value while addressing real-world banking challenges.
Key Responsibilities
Client Advisory & Strategic Consulting
- Partner with banking clients to identify, analyze, and prioritize opportunities for Agentic AI transformation across corporate banking functions
- Conduct strategic assessments to evaluate AI readiness, change capacity, and value potential within client organizations
- Develop business cases, ROI analyses, and value realization frameworks for AI initiatives
- Advise C-suite and senior banking executives on AI adoption strategies, operating model impacts, and transformation roadmaps
Business Analysis & Requirements Engineering
- Lead discovery workshops and stakeholder interviews to capture business needs, pain points, and success criteria
- Analyze and map complex banking processes (e.g., client onboarding, trade finance operations, cash management, compliance workflows)
- Translate business requirements into detailed user stories, use cases, and functional specifications for AI solutions
- Define key performance indicators (KPIs), success metrics, and monitoring frameworks for AI implementations
Solution Design & Value Realization
- Collaborate with solution architects and technical teams to ensure business requirements are accurately reflected in technical designs
- Design target operating models and business processes optimized for AI-enabled operations
- Develop change impact assessments, adoption strategies, and stakeholder engagement plans
- Create business-facing documentation, training materials, and user guides for AI solutions
Industry & Domain Leadership
- Maintain deep understanding of corporate banking trends, competitive landscape, and regulatory environment
- Conduct market analysis on AI applications in banking and synthesize insights for client recommendations
- Develop thought leadership content, white papers, and case studies on AI transformation in banking
- Serve as subject matter expert on banking operations during solution design and implementation
Top Skills
What We Do
Zero distance innovation for GenAI creators and industries Expertly engineering platforms and curating multimodal, multilingual data, we empower the ‘Magnificent Seven’ and enterprise clients with safe, scalable AI deployment We a team of over 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We bring platforms, partners and 1.8 million vertical domain experts to create high-quality pre-trained datasets, fine-tuned industry-specific LLMs, and RAG pipelines supported by vector databases. These innovations can reduce GenAI costs by up to 80% and bring GenAI solutions to market 50% faster in 230 locales.
