Sr. Forward Deployed AI Engineer (Remote Eligible in Germany)

About this role

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role.

You Will:

• Lead complex, multi-system AI deployments end-to-end — scoping, architecting, building, validating, and managing the customer relationship throughout the full engagement lifecycle, applying sustained analytical thinking and independent judgement at each stage.

• Own the AI workshop programme for your pod, customising modules per customer, leading technical sessions, translating outputs into production requirements, and continuously evolving content from field learning — this requires careful planning, prioritisation, and the ability to manage multiple concurrent workstreams.

• Architect multi-agent solutions, selecting the right coordination pattern for each customer's workflow characteristics and compliance requirements, drawing on deep expertise in system design and enterprise-scale AI services.

• Design client-specific and industry-specific MCP resource packs that serve personalised intelligence from the server so every connected AI surface grows smarter for that customer automatically, handling sensitive customer data and documentation with strict confidentiality and accuracy.

• Own Deployment Kit quality for your pod, ensuring every kit is documented to a standard that a solutions consultant with no engineering background can follow independently — if it is not clear enough to hand off, it is not finished.

• Lead Solutions Enablement Sprints, transferring AI deployment patterns to solutions consultants and partners through structured training materials and certification criteria, drawing on strong interpersonal and communication skills to make complex technical concepts accessible across varied audiences.

• Drive the intelligence loop: author strategic memos, present field findings weekly, contribute Agent Bricks and Skills, and file RFCs for platform improvements — this requires clear written and verbal communication and the ability to synthesise field observations into actionable insight for senior stakeholders.

• Mentor junior Field Deployment Engineers on customer engagements, code reviews, and Deployment Kit quality, fostering a collaborative team environment where knowledge is shared and people grow in their technical ownership and confidence.

• Collaborate with solutions consultants and partners across the organisation, managing relationships with both technical and non-technical stakeholders including security reviewers and senior customer leadership such as CIOs.

• Navigate the cognitive complexity of simultaneously managing multiple enterprise customer engagements, each with distinct technical architectures, compliance requirements, and stakeholder dynamics, maintaining rigorous attention to detail under pressure.

• Work with ambiguity and resilience in a fast-moving field where AI tooling, frameworks, and customer expectations are evolving rapidly, sustaining high-quality output while managing the psychosocial demands of high-stakes enterprise deployments.

• Work within Smartsheet's platforms, tools, and infrastructure including cloud environments, AI services, agent frameworks, and internal deployment tooling, taking responsibility for the quality and reliability of the systems and assets you build and maintain.

• Travel domestically and internationally approximately 25–50% of the time to support customer engagements, workshops, and field sessions.

• Perform standard computer and keyboard use in a remote working environment, with extended screen use consistent with a sedentary, office-based role conducted from a home or co-working setting.

You Have:

• 6–10+ years of production software engineering experience, including at least 3 years deploying AI and ML systems to production, with deep expertise in Python and strong proficiency in TypeScript and JavaScript — demonstrating the depth of technical knowledge and educational foundation expected at principal level.

• A proven track record leading complex enterprise technical engagements, including managing customer relationships, navigating security reviews, and delivering production systems that organisations depend on — this may be evidenced through equivalent industry experience as well as formal qualifications.

• Deep production LLM experience spanning multi-agent orchestration, MCP and tool-use patterns, RAG optimisation, evaluation frameworks, and agent deployment at scale.

• System architecture expertise across enterprise systems, cloud infrastructure, and AI services, with the ability to communicate architectural decisions clearly to both a CIO and a junior engineer.

• Demonstrated ability to create reusable technical assets that others use in production — the ability to think in platforms rather than individual projects is essential to this role.

• Strong written and verbal communication skills evidenced through architecture documents, runbooks, strategic memos, and training materials; Deployment Kits produced in this role serve as a direct portfolio of that communication quality.

• A consiste

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