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Forward Deployed Engineer - AI Solutions (Gracenote Division)

Published · Updated

Pay not postedRemote, hiring in Oregon

Leads technical pre-sales and implementation for Gracenote’s API and AI products, helping enterprise clients integrate entertainment metadata into LLM-powered discovery experiences.

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View posting at The Nielsen Company

At a glance

Posted base pay

Not posted

The work

Builds what the customer runs

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales
  2. Proof of concept
  3. Implementation
  4. Operations (not covered)

Travel Up to 40%

Coding
Prototypes and scripts
Builds for
External customers
Role
Individual contributor

What they ask for

Tools

  • Model Context Protocol
  • JSON-RPC 2.0
  • AWS Cognito
  • Google ADK
  • AWS Bedrock Agents
  • LangChain
  • LlamaIndex
  • Python
  • TypeScript
  • Google Cloud Vertex AI

Less common in FDE jobs

  • Coding work: Prototypes and scripts5%
  • Covers pre-sales24%
  • Fully remote30%
  • Covers proofs of concept38%

Share of US FDE postings that state each fact.

What you’ll do

  • Lead customer discovery, technical consultation, and AI solution proof of concepts.
  • Build focused AI agents that demonstrate Gracenote Video MCP Server capabilities.
  • Recommend integration architectures and validate new MCP tools as Customer Zero.
  • Guide client developers through implementation, including JSON-RPC 2.0 integration.

What you’ll bring

  • Practical experience with MCP tooling, agent deployment, JSON-RPC 2.0, and AWS Cognito.
  • Experience building with Python or TypeScript/Node.js and integrating B2B enterprise APIs.
  • Experience with agent frameworks such as Google ADK, AWS Bedrock Agents, LangChain, or LlamaIndex.
  • Knowledge of OAuth/OIDC, enterprise security, and data privacy requirements.

View posting at The Nielsen Company

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Pay and conditions

Posted pay
Pay not posted
Location
Remote, OR
Work arrangement
Remote
Employment type
Full-time
Travel
Up to 40%