Sr. Product Solutions Architect - Gracenote

Company Description

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future

Job Description

Gracenote is an entertainment data and technology provider powering the world’s top music services, automakers, cable and satellite operators, and consumer electronics companies. At its core, Gracenote helps people find, discover and connect with the entertainment they love. Daily, Gracenote processes 35 billion rows of data and is quickly becoming a world-leader in return path “big data.” Over the past 3 years, the company has grown to more than 2000 employees in 17 countries, including over 600 of the world’s top engineers with a passion for music, video, sports, and entertainment technology. Founded in 1998, Gracenote is one of America’s most iconic and respected media companies.

We are seeking a technical, customer-focused Product Solutions Architect to lead customer technical pre-sales and implementation for our suite of metadata products and AI products, including the Gracenote Model Context Protocol (MCP) Servers. You will serve as the primary technical subject matter expert for the Gracenote suite of products, enabling B2B clients to successfully integrate our authoritative metadata into their discovery experience including AI-powered integrations. You will lead the end-to-end customer technical engagement lifecycle of technical solutions, from pre-sales consultation, requirements gathering, product solutioning and  proof-of-concept development to post-implementation support and strategic product advocacy.
 
Key Responsibilities

• Technical Pre-Sales & Strategy: Partner with Sales to lead technical discovery sessions, assessing client needs and demonstrating the value of Gracenote’s solutions. Blending standard solution selling with AI/MCP value propositions, you will identify tangible ways Gracenote products can improve discovery experiences. Lead technical workshops, PoCs and own customer integration planning through adoption and production deployment.

• Implementation & Delivery: Act as the technical anchor during onboarding, guiding developers through integration of Gracenote metadata available via standard APIs and Agentic frameworks. Provide code-level guidance, document integration use cases, and ensure best practices for deployment on frameworks like Google or AWS.

• Operational & Strategic Advocacy: Function as the "voice of the customer" to influence product roadmaps. Translate customer requirements into actionable requests to the product team. Update or create technical documentation to drive customer self-sufficiency. Serve as "Customer Zero" to test and validate new products before rollout. 

• Technical Development: Design, build, and maintain focused, single-purpose AI agents that demonstrate technical capabilities of the Gracenote MCP Server. Support PoCs involving standard API/XML data integration alongside modern AI-genetic engineering (function calling, token optimization, and context management).

Qualifications

• Experience: 3-5+ years in pre-sales, customer-facing technical engineering or solutions architecture roles. Specific experience designing, deploying, or observing AI agents, MCP architectures, and managing cloud framework deployments (AWS/Google/Azure) is highly preferred. Experience in the TV industry is a strong advantage, but not required.

• Technical Proficiency: Strong foundation in Restful APIs, SQL, ETL, and structured data formats (JSON/XML). Understanding of modern AI-based tech stacks, including tool chaining, prompt engineering, and authorization management (e.g., OAuth).

• Consultative Skills: Proven ability to bridge the gap between complex architectures and business objectives. Expert communication skills for diverse audiences, including C-level executives, business contacts, and engineering teams. 

• Logistics: Ability to travel to customer sites, primarily in North America up to 30% of the time to conduct workshops and discovery sessions.  Periodic International travel may be required.

Additional Information

Enabling