$185,000–$225,000
Forward Deployed Engineer - AI Solutions (Gracenote Division)
Updated
Pay not postedRemote, hiring in Oregon
This customer-facing Product Solutions Architect role leads technical pre-sales, proof-of-concept development, and implementation of Gracenote’s API and AI products for global enterprise clients.
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At a glance
Posted base pay
Not posted
Median $190K
Typical senior FDE payMiddle 50% of 1,803 postings$160K–$220KThe work
Builds what the customer runs
Balance
- Mostly building
- Mixed
- Mostly pre-sales or support
Project stages
- Pre-sales
- Proof of concept
- Implementation
- Operations (not covered)
Travel Up to 40%
- Coding
- Prototypes and scripts
- Builds for
- External customers
- Level
- Senior
- Role
- Technical lead
What they ask for
Tools
Less common in FDE jobs
- Coding work: Prototypes and scripts5%
- Covers pre-sales25%
- Fully remote28%
- Covers proofs of concept40%
Share of US FDE postings that state each fact.
What you’ll do
- Lead technical discovery, consultation, pre-sales, and proof-of-concept engagements with enterprise customers
- Design and build focused AI agents using Gracenote Video MCP Server capabilities
- Recommend integration architectures and guide developers through API and JSON-RPC 2.0 adoption
- Validate new MCP tools as Customer Zero and influence product roadmaps through customer feedback
What you’ll bring
- Practical experience with MCP tooling, MCP primitives, JSON-RPC 2.0, and AWS Cognito
- Experience designing or deploying multi-step AI agents with Google ADK, AWS Bedrock Agents, LangChain, or LlamaIndex
- Strong Python or TypeScript/Node.js experience supporting proofs of concept and enterprise API integrations
- Experience with enterprise security, OAuth/OIDC, data privacy, and managed foundation models
View posting at The Nielsen Company
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