Senior Forward Deployed AI Engineer (remote Eligible in the Uk)

Smartsheet Smartsheet · Seattle · United Kingdom · Engineering - Developers

Senior AI Engineer focused on deploying complex, multi-system AI solutions end-to-end for enterprise clients. This role involves architecting multi-agent systems, designing personalized AI resources, and creating deployment kits. The engineer will also mentor junior team members, contribute to AI strategy, and drive improvements to the AI platform.

What you'd actually do

  1. Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout.
  2. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning.
  3. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements.
  4. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically.
  5. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done.

Skills

Required

  • Python
  • TypeScript
  • JavaScript
  • LLM experience
  • multi-agent orchestration
  • tool-use
  • RAG optimisation
  • evaluation frameworks
  • agent deployment at scale
  • System architecture
  • enterprise systems
  • cloud infrastructure
  • AI services
  • reusable technical assets
  • communication

Nice to have

  • founding or scaling an FDE/solutions engineering function
  • Technical founder background
  • Databricks
  • AWS Bedrock
  • Temporal
  • healthcare domain knowledge
  • financial services domain knowledge
  • government domain knowledge
  • Agent framework contributions (Strands SDK, LangChain, open-source MCP servers)
  • German language proficiency
  • French language proficiency
  • AI governance
  • AI ethics
  • regulatory requirements (e.g. GDPR, UK/EU AI Act)

What the JD emphasized

  • 6–10+ years production software engineering, including 3+ years deploying AI/ML to production.
  • Deep production LLM experience: multi-agent orchestration, MCP/tool-use, RAG optimisation, evaluation frameworks, agent deployment at scale.
  • System architecture expertise spanning enterprise systems, cloud infrastructure, and AI services explainable to a CIO and a junior engineer.
  • Demonstrated ability to create reusable technical assets that others use in production. You think in platforms, not projects.

Other signals

  • Deploying AI/ML to production
  • multi-agent orchestration
  • agent deployment at scale
  • creating reusable technical assets