Senior Staff Engineer - GenAI Engineer

1 Week ago • 4-8 Years • Artificial Intelligence • Game AI • Undisclosed

About the job

Job Description

As a Senior Staff Engineer - GenAI Engineer, you will design end-to-end generative AI architectures for enterprise solutions, collaborating with various teams. You'll lead solution architecture for early-stage projects, preparing them for funding. Responsibilities include AI governance and risk assessment, ensuring Responsible AI implementation, and collaborating cross-functionally. You'll act as a subject matter expert, facilitating knowledge sharing, and developing strategic roadmaps aligned with company vision. Staying current on industry trends is crucial for driving innovation.
Must have:
  • Python (Strong)
  • Generative AI Fundamentals (Strong)
  • End-to-End Generative AI Architecture Design
  • Solution Architecture for Early-Stage Projects
  • AI Governance and Risk Assessment
Good to have:
  • Microservices architecture (MSA)
  • Azure DevOps

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (19000+ experts across 33 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

End-to-End Generative AI Architecture:

  • Collaborate with digital teams, architects, stakeholders, and platform teams to design comprehensive AI architectures for enterprise solutions developed by the AI CoE.
  • Work closely with teams like Team Builder, Career Development (CD) Platform, and RevOps to deliver cohesive, efficient AI-driven solutions.

Solution Architecture for Early-Stage Initiatives:

  • Lead the solution architecture design for early-stage generative AI projects, guiding proof-of-concept (PoC) and prototype development in partnership with the AI CoE.
  • Prepare and validate these projects for the Investment Committee (IC) funding stage.

AI Governance and Risk Assessment:

  • Engage with the AI Governance setup and Enterprise Architecture CoE to evaluate ongoing generative AI solutions across digital teams, identifying and flagging risks related to technical debt, non-standard stack usage, or overlapping initiatives.
  • Review planned generative AI IC proposals, working with the Enterprise Architecture CoE to validate each project's alignment with AI standards, including considerations for build-vs-buy decisions, technology stack compatibility, and long-term feasibility.

Responsible AI Implementation:

  • Collaborate with the Generative AI Platforms team to ensure Responsible AI guardrails, best practices, and standards are integrated into large language model (LLM) evaluations and generative AI applications, promoting safe and ethical AI deployment.

Cross-Functional Collaboration:

  • Act as a subject matter expert on generative AI, effectively engaging with and guiding cross-functional teams, including digital, platform, and governance stakeholders.
  • Facilitate knowledge sharing, establish best practices, and contribute to a collaborative AI-driven culture.

Strategic Planning & Innovation:

  • Develop and implement architectural strategies and roadmaps that align with the company's vision and technology advancements.
  • Stay current with industry trends to drive innovation and integrate best practices in generative AI architecture.

Qualifications

Must have Skills: Python (Strong), Generative AI Fundamentals (Strong)

Good To Have Skills: Microservices architecture (MSA) (Capable), Azure DevOps (Capable).

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