Head of Artificial Inteligence

We are seeking a Head of Artificial Intelligence with an executive vision and deep technological expertise to lead our Consulting and Innovation practice within the Banking, Financial Services, and Insurance (BFSI) sector. This leader will be responsible for defining large-scale AI adoption strategies (including Generative AI, Copilots, and Autonomous Agents), establishing robust governance frameworks, and ensuring financial (ROI) and operational value realization for highly complex enterprise clients. The professional will act as a strategic bridge between data engineering, solution architecture, and C-Level business objectives.

1. Technical Competencies (Hard Skills)

• AI Strategy & Architecture: Deep knowledge in designing and structuring data journeys and platform architectures (Data Lakes, multi-cloud AWS/Azure, Databricks, Snowflake) tailored to support scalable AI and Machine Learning operations.
• BFSI Industry Expertise: Solid understanding of market dynamics, regulatory compliance (e.g., GDPR/LGPD, Central Bank regulations, Open Finance), and specific use cases within the financial and insurance sectors (e.g., fraud detection, risk modeling, algorithmic trading, credit personalization, and back-office automation).
• AI Governance & FinOps: Proven ability to develop and implement AI Governance policies (Responsible AI, bias mitigation, data security) and FinOps strategies to optimize the computational cloud costs associated with Large Language Models (LLMs).
• Consulting & Pre-sales (RFP/RFI): Extensive experience providing technical and consultative leadership during competitive bidding processes (RFPs). Strong ability to conduct critical requirements analysis, generate structured RFIs, and draft high-impact technical and commercial proposals.
• Engineering & Software Development Life Cycle (SDLC): Advanced knowledge in integrating "hybrid squads" (collaboration between human developers and digital agents/Copilots) into the software development life cycle and IT operations.

2. Behavioral Competencies (Soft Skills)

• Business Acumen & Value Realization: Exceptional ability to translate complex technical capabilities into clear business value levers, defining OKRs/KPIs and building compelling Business Cases that demonstrate the Return on Investment (ROI) of AI initiatives.
• Executive Leadership & Influence: Consultative posture with the ability to seamlessly navigate and communicate at the C-Level, acting as a genuine Trusted Advisor to enterprise clients.
• Change Management: Strong capability to lead organizational transformations, evangelizing the responsible use of Artificial Intelligence and mitigating cultural resistance regarding the adoption of disruptive technologies.
• Analytical & Problem-Solving Skills: Sharp critical thinking skills to diagnose operational bottlenecks in complex corporate ecosystems and propose viable, secure, and scalable technological solutions.
• Mentorship & Team Building: A strong vocation for acting as a leader and educator in developing internal talent, including designing competency matrices and training curricula to shape the next generation of Data and AI specialists.

3. Desirable Competencies (Nice-to-Have)

• Advanced Academic Background: Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, Applied Mathematics, Statistics, or related fields (e.g., specialization in Bayesian Probabilistic Models for risk analysis).
• Cloud & Data Certifications: Active architecture-level certifications (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert) or specializations in modern data platforms (Snowflake, Databricks).
• Thought Leadership: Active presence in the technology industry, whether through published papers, speaking engagements at major tech events, or active contributions to open-source technology consortiums.
• Strategic Partnership Management: Prior experience developing and managing strategic alliances with major technology players (e.g., Microsoft, Google, AWS, OpenAI) to co-create joint market solutions.

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Master's or PhD in CS/AI/Mathematics
AI Strategy, Governance & FinOps, Consulting & Pre-sales, SDLC & Hybrid squads, Data Lake & Cloud Architecture
Define large-scale AI adoption strategies for enterprise clients., Establish governance frameworks and ROI realization., Bridge data engineering, solution architecture, and C-level objectives., Lead consulting and pre-sales during bids and RFPs., Mentor teams and shape internal AI talent.