3 months ago

Sr. Forward Deployed AI Engineer (Remote Eligible in the UK)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Lead complex, end-to-end AI deployments across multiple systems, architect multi-agent solutions, and produce reusable technical assets. Drive field enablement, mentor junior engineers, and manage customer relationships through production deployments. This role focuses on scalable AI services, MCP resources, and deployment kits for a broad Solutions org, with travel and UK work eligibility.

Location: United Kingdom

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout.
•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.
•Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements.
•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.
•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.

Travel: Medium travel

Key Requirements

•6–10+ years of production software engineering, including 3+ years deploying AI/ML to production; deep Python; strong TypeScript/JavaScript
•Proven track record leading complex enterprise technical engagements; able to manage customer relationships, navigate security reviews, and deliver production systems
•Deep production LLM experience: multi-agent orchestration, MCP/tool-use, RAG optimization, evaluation frameworks, agent deployment at scale
•System architecture expertise spanning enterprise systems, cloud infrastructure, and AI services explainable to a CIO and junior engineer
•Demonstrated ability to create reusable technical assets that others use in production; think in platforms, not projects

Experience:6-10 yearsAI/MLEnterpriseCloudPythonJavaScript

Skills:PythonTypeScriptJavaScriptLLMMulti-agentProduction deploymentsCloud infrastructureAI services

Languages:English

Tech Stack:PythonTypeScriptJavaScriptLLMMulti-agentMCPRAGProductionCloud

Company Brief

Smartsheet

Provides a cloud-based work management platform that enables teams to plan, track, automate, and report on work. Smartsheet combines spreadsheets, collaboration, and workflow automation to help organizations manage projects and processes at scale.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bellevue, United States

Founded: 2005

Website LinkedIn

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Smartsheet

3 months ago

Sr. Forward Deployed AI Engineer (Remote Eligible in the UK)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: United Kingdom

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout.
•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.
•Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements.
•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.
•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.

Travel: Medium travel

Key Requirements

•6–10+ years of production software engineering, including 3+ years deploying AI/ML to production; deep Python; strong TypeScript/JavaScript
•Proven track record leading complex enterprise technical engagements; able to manage customer relationships, navigate security reviews, and deliver production systems
•Deep production LLM experience: multi-agent orchestration, MCP/tool-use, RAG optimization, evaluation frameworks, agent deployment at scale
•System architecture expertise spanning enterprise systems, cloud infrastructure, and AI services explainable to a CIO and junior engineer
•Demonstrated ability to create reusable technical assets that others use in production; think in platforms, not projects

Experience:6-10 yearsAI/MLEnterpriseCloudPythonJavaScript

Skills:PythonTypeScriptJavaScriptLLMMulti-agentProduction deploymentsCloud infrastructureAI services

Languages:English

Tech Stack:PythonTypeScriptJavaScriptLLMMulti-agentMCPRAGProductionCloud

Company Brief

Smartsheet

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bellevue, United States

Founded: 2005

Website LinkedIn