Senior Forward Deployed AI Engineer (remote Eligible in Germany)

Smartsheet Smartsheet · Seattle · United Kingdom · Engineering - Developers

Senior AI Engineer focused on leading complex, end-to-end AI deployments for enterprise clients, architecting multi-agent solutions, and enabling partners. The role involves customer engagement, building reusable assets, and mentoring junior engineers, with a strong emphasis on production LLM experience and system architecture.

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 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 orchestration
  • tool use
  • RAG optimization
  • evaluation frameworks
  • agent deployment at scale
  • enterprise systems architecture
  • cloud infrastructure
  • AI services
  • communication
  • technical writing
  • mentoring

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
  • Proven track record leading complex enterprise technical engagements
  • Deep production LLM experience
  • System architecture expertise
  • Demonstrated ability to create reusable technical assets

Other signals

  • leading complex AI deployments
  • architect multi-agent solutions
  • deploying AI/ML to production
  • customer relationships
  • enterprise systems