Base: up to $300,000; bonus/equity: discretionary ...
On-site
Ai/data platform architecture
Mlops, llmops, agentops pipelines
Genai industrialization
This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom
Job Summary
This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom.
You will personally shape the architecture of mission-critical AIML platforms, often in first-party tech stack, and develop/drive the team of ICs who bring them to life.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
Matching Summary
This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom.
Salary
Base: up to $300,000; Bonus/Equity: discretionary bonus; Benefits: health, dental, vision, life insurance, disability plans, 401(k), 11 paid holidays, 12 weeks Parental Leave, free time PTO
Skills & Requirements
Must-have
AI/Data platform architecture
MLOps, LLMOps, AgentOps pipelines
GenAI industrialization
Client-facing engineering leadership
Hands-on architecture
Executive presence
Team leadership
Embedded delivery
Nice-to-have
Experience in TMT vertical
FDE-style or embedded delivery
Comfort with ambiguity
Personal reputation for architectural clarity
Contributions to ML/AI community
Key Requirements
15–20 years of experience
Deep hands-on experience deploying AI/ML/GenAI
Demonstrated executive presence
Ability to whiteboard fluently under pressure
Experience operating within client-owned or non-standard technology stacks