SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
ServiceNow's Applied AI Forward Deployed Engineering (FDE) team partners with strategic enterprise customers to design, build, and deploy AI-native solutions that solve mission-critical business challenges. As a Senior Forward Deployed Solution Engineer, you will act as the technical leader (CTO of the build) for customer engagements, owning the full stack from backend services and LLM pipelines to front-end integrations.
You will embed directly with customer teams in the field, working in agile sprints to deliver production-ready, AI-enabled applications. Your responsibilities include:
• Design and implement end-to-end LLM-enabled solutions spanning backend logic, data orchestration, vector databases, and UI components
• Operate in live customer environments, adapting and iterating solutions in real-world contexts
• Build reusable assets—libraries, prompt templates, SDKs, and scaffolds—that accelerate future engagements and scale success across the customer base
• Debug and optimize distributed systems for latency, reliability, and observability
• Influence platform strategy by sharing field-tested insights and extensible code patterns with internal product and platform teams
• Integrate with legacy enterprise systems while maintaining security and compliance in regulated environments
• Travel up to 30% to embed onsite with customers and deliver high-stakes implementations
Success is measured by production-grade deployments that scale, reusable patterns that power multiple projects, platform influence that shapes internal tooling, and your ability to move fast without breaking things in high-stakes contexts.
QUALIFICATIONS:
Required:
• 10+ years of software engineering experience, including 2+ years in customer-facing or embedded roles
• Proven ability to design and implement AI-native software in production environments
• Strong backend engineering (Python, Node.js, or Java) and frontend skills (React, Angular)
• Experience with REST/GraphQL APIs and system architecture
• Familiarity with LLM tooling: LangChain, Semantic Kernel, prompt chaining, vector search, and context management
• Proficiency debugging distributed systems, tuning for latency, and implementing monitoring/observability
• DevOps fluency: AWS, Azure, or GCP deployment experience with CI/CD, containers, and infrastructure-as-code
• Platform mindset: ability to contribute to shared SDKs and tools that raise engineering velocity
• Product sensibility: prioritize for user value, MVP iteration, and long-term scalability
• Experience leveraging or critically thinking about AI integration into work processes, decision-making, or problem-solving
• Willingness to travel up to 30% for onsite customer engagement
Preferred:
• Experience integrating AI into SaaS platforms (ServiceNow, Salesforce, or similar)
• Track record of production deployments in secure, regulated enterprise environments
• Contributions to developer experience tooling, frameworks, or reusable AI scaffolds
