Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience.
Strategic Engineering Leadership: Proven experience leading large-scale engineering organizations through product transformation initiatives (e.g., platform modernization, cloud migration, operating model changes).
Demonstrated success in setting vision and executing across complex, multi-year technology programs.
Demonstrated strength in partnership-building and cross-functional collaboration.
Able to influence and align product teams, platform/infrastructure teams, and governance bodies around a common vision and roadmap.
Ability to operate in complex market and organizational contexts, translating strategic objectives into actionable plans.
Proven track record of driving innovation, navigating ambiguity, and delivering measurable outcomes at scale.
AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency and scale, while keeping expert human judgment in critical loops to ensure quality and trust.
Platform Over People: Prioritizes building robust platforms and automation over relying on individual heroic efforts, enabling sustainable and scalable growth.
Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive portal for all their needs, simplifying access and support.
Standardization Everywhere: Drives consistency in tools, processes, and data across the board, reducing complexity and improving interoperability and maintainability.
Self-Service as the Default: Champions self-service capabilities, empowering users to accomplish tasks independently (from data ingestion to model deployment) without bespoke engineering work.
Deep Co-Ownership with PMG: Fosters a culture of partnership with the Portfolio Management Group, aligning closely on priorities, sharing roadmaps and KPIs, and co-owning outcomes to ensure the platform truly meets investment teams' needs.
Alpha generation workflows or closely related quantitative research processes in finance/investments.
Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray).
API-first platform design and developer experience best practices.
AI/ML applications for workflow automation, data validation, and operational excellence
Modern stack knowledge and skills - e.g. Python, Polars, Ray, MLFlow or equivalent technology

SmartExplore AI is experimental.

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Test Engineering Technician - AI Data Center Systems (Servers & GPUs)

Advanced Micro Devices

Secaucus, NJ 07094

~ 18 min Onsite

Ability to lift up to 35 pounds
Safely climb ladders
Wear personal protective and ESD gear correctly
Stand and walk throughout the facility for extended periods without loss or reduction of productivity

SmartExplore AI is experimental.

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