Lead Software Engineer (Sr AI Architect)

Reports To: VP of Cloud Governance, Infrastructure, and Emerging Technologies

Strategic Mandate

As the Lead AI Solutions Architect/Engineer, your mission is to architect the technical foundation for Nielsen’s AI-driven evolution. You are not just building tools; you are industrializing AI—transitioning experimentals POCs into enterprise-grade, governed, and scalable engineering solutions. Reporting into the Infrastructure and Emerging Technologies braintrust, you will bridge the gap between complex business requirements and modern, cloud-native deployments.

The Bottom Line

You will provide high-level expertise in solving unique, complex problems with broad impact on the business. You are responsible for designing and implementing AI solutions that range from Databricks modules to advanced Agents in Gemini and Glean. Your focus is unblocking teams and moving projects forward with minimal friction.

Core Goals

AI Industrialization: Architect and deploy LLM orchestration and vector database solutions at scale.

Stakeholder Enablement: Partner with AI Product Managers and functional leads across AM/GN Tech to translate business opportunities into technical outcomes.

Evangelism & Community: Lead the "AI braintrust" by guiding engineers and building a robust community of AI and data product developers.

Governance Integration: Ensure every proposed solution mentions FinOps (cost) and Governance (risk) implications automatically.

Expertise Areas & Skills

Domain Authority: Technically precise in LLM orchestration, Python, Java, and LangChain.

Platform Mastery: Advanced implementation experience with AWS Bedrock agent capabilities, Gemini, and ChatGPT.

Operational Pragmatism: Experience building and successfully rolling out products in a fast-paced environment.

Consultative Communication: Fluent English with the ability to challenge assumptions and identify strategic blind spots.

Rules of Engagement

Precision over Prose: We value high-density language and scannable updates.

Decision Support: Don't just provide options; recommend the path that balances rapid innovation with fiscal responsibility.

Risk-First Mentality: Proactively identify performance bottlenecks and architectural risks before they impact the business.