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We are seeking a visionary Distinguished Engineer to drive our AI-First Transformation, bridging the gap between AI technology and business impact. You will re-imagine how our enterprise operates by rewriting operational workflows to drive efficiency, personalization, and speed. Your goal is to build a scalable 'AI Factory' that moves the organization from ad-hoc pilots to industrialized business value by leading the end-to-end AI lifecycle and translating ideas into tangible business outcomes.
Job Responsibility:
Define the AI transformation roadmap, ruthlessly prioritizing initiatives like autonomous agents and predictive operations to ensure a clear path to ROI
Oversee the data strategy, curating 'Golden Examples' from institutional history to train models on our best work and digitize our 'Enterprise Memory'
Re-imagine and design 'Invisible AI' workflows that seamlessly assist human experts, rather than simply digitizing existing processes
Establish rigorous 'Report Cards' for AI models to move from 'vibes-based' decisions to structured evaluation, measuring accuracy, latency, and business relevance before production
Partner with Legal, InfoSec, and Engineering to implement strict governance and safety 'Circuit Breakers,' protecting company IP and preventing data leaks or unsafe AI actions
Own the adoption curve and unit economics, ensuring workforce trust in AI tools and preventing model decay by maintaining a fresh knowledge base
Requirements:
Bachelor's degree with 15 years of related experience, or Master's degree with 12 years of experience, or PhD with 8 years of experience
Deep experience leading cross-functional teams at the intersection of Business Strategy and Technical Execution
Proven 'General Manager' mindset with a track record of owning the P&L or business outcome of a digital product
Fluency in the modern AI stack, understanding the capabilities and limitations of LLMs, RAG architectures, and Agentic workflows
Nice to have:
Ability to translate complex concepts between CXOs (Business Outcomes), CIOs (Architecture/Security), and Data Scientists (Models/Weights)
Technical fluency to design workflows that handle ambiguity and require human-in-the-loop validation
Demonstrated success in change management, driving technology adoption, managing automation concerns, and upskilling teams