Hi R***, I hope you’re doing well. I’m J***e, an HR recruiter at StrategyBrain, and I came across your impressive work at G***I,especially your leadership in architecting and deploying large-scale generative AI and NLP systems. We’re partnering with N***s to hire a Head of Generative AI and ML Architecture, a role that would leverage your deep experience in LLM pipelines, inference optimization, and MLOps at scale. If this sounds like a fit for your next career step, I’d love to share more details and hear about your interests.

Hi R***, great to hear you’re interested. Here’s a bit more on the team, challenges and next steps: Team & Environment • You’ll lead the Generative AI & ML Architecture practice at N***s, partnering with a global organization of 300+ engineers and researchers. Your direct reports will include senior AI architects, MLOps engineers and data scientists. You’ll work closely with Product, Cloud Infrastructure and Research to bring GenAI capabilities into enterprise solutions. • We have fully managed GPU clusters, Kubernetes-based deployment pipelines and partnerships with A***S/G***P to support rapid experimentation and scale. Key Challenges 1. Strategic Roadmap: Define and execute our multi-year GenAI roadmap,identifying high-impact use cases, selecting model families (LLMs, multimodal, retrieval-augmented), and driving adoption across business units. 2. Scalability & Performance: Architect pipelines that serve millions of requests per day with sub-second inference, leveraging model optimization (distillation, quantization) and dynamic autoscaling. 3. MLOps Maturity: Build and refine CI/CD frameworks for data, code and model versioning, automated testing, drift monitoring and rollback processes. 4. Team Enablement: Mentor engineers on best practices, run regular design reviews, and foster a culture of innovation and continuous improvement. Growth & Impact • You’ll be a key member of the Technology Leadership Team, shaping both product vision and engineering strategy. • We offer a clear path to VP or Head of AI roles, with sponsorship for conferences, advanced training, and a generous R&D budget for prototyping. • Compensation includes a competitive base salary, performance bonus and meaningful equity,aligned with your experience and the business impact you drive. Next Steps If this sounds aligned with your goals, I’d love to set up a 30,45 minute call with our VP of Engineering later this week. Do you have availability on Thursday or Friday? And of course, happy to answer any questions you have about the role, team or organization.

Hi R***, Thanks for asking. For this Head of Generative AI & ML Architecture role, we’re targeting a base salary in the $250K,$300K range (depending on experience), plus a performance bonus of approximately 20,30% and a meaningful equity package. As for work location, N***s operates on a hybrid model out of our San Francisco office,typically 2,3 days onsite per week with remaining days remote. Does that align with your expectations? If so, would Thursday at 2:00 PM PT or Friday at 10:00 AM PT work for our 30,45 minute call with the VP of Engineering? Looking forward to your thoughts. Best, J***e

Hi R***, Glad to hear the range and hybrid model work for you. For this role we’re targeting a meaningful equity grant in the range of 0.5%,1.0% of fully diluted shares (exact sizing will depend on experience and final title). Our standard vesting is over four years with a one-year cliff and monthly vesting thereafter, plus eligibility for annual refresh grants tied to performance milestones. I’ve locked in Thursday at 2:00 PM PT for your 30,45 minute conversation with our VP of Engineering,look out for a calendar invite shortly. Please let me know if you need anything else beforehand. Best, J***e

Hi R***, Great question. Our annual equity refresh grants are designed to reward continued impact and align with both company and individual performance. Here’s how it typically works: • Timing: Your first refresh grant becomes eligible at your one-year work anniversary, with subsequent grants awarded annually shortly after our fiscal-year performance review cycle (usually Q1). • Size: Refreshes generally range from 10% to 25% of your original grant size, scaled to role, level and the year’s objectives. • Milestones: We tie refresh grants to a mix of company-wide and individual goals, for example: , Successful delivery of your multi-year GenAI roadmap milestones (e.g., launching retrieval-augmented pipelines or multimodal proof-of-concepts) , Achieving target performance gains (such as sub-second inference at scale or a defined percentage reduction in GPU costs) , MLOps maturity metrics (automated CI/CD coverage, deployment frequency, drift detection thresholds) , Leadership and team-enablement outcomes (mentorship goals, design-review cadence, cross-team adoption). Of course, the specifics will be calibrated with you and our VP of Engineering during your first year. We’ll review your progress each spring and adjust refresh sizing based on achieved results and next-year targets. Hope that clarifies,let me know if you’d like any more detail before we connect on Thursday at 2 PM PT. Looking forward to the conversation! Best, J***e

Hi R***, For a Head-level role that consistently hits its GenAI roadmap milestones, refresh grants tend to land toward the upper end of that 10,25% range,think roughly 15,20% of your original grant in year two, with top performers sometimes seeing closer to 25%. As for goal granularity, we typically blend broad company-level objectives (e.g., overall revenue growth from GenAI offerings, market adoption metrics) with highly specific individual targets. In practice that looks like: • Company Goals (40,50% of your performance score): , Annual revenue or customer-adoption thresholds , Key strategic launches (e.g., first multimodal proof-of-concept in Q3) • Individual Goals (50,60%): , Delivery of defined roadmap milestones (e.g., live retrieval-augmented pipelines by mid-year) , Quantifiable performance improvements (sub-second inference at scale, 20% GPU cost reduction) , MLOps KPIs (CI/CD coverage >90%, deployment frequency, drift-alert SLAs) , Team-enablement metrics (mentor X engineers, lead Y design reviews, cross-team adoption rates) This split ensures you’re driving both the big-picture business impact and the day-to-day technical wins that keep us ahead in GenAI. Looking forward to diving deeper with our VP of Engineering on Thursday at 2:00 PM PT. Let me know if you need anything else beforehand! Best, J***e