Forward Deployed Solution Engineer – Applied AI FDE

ServiceNow • New York, NY

16h

About The Position

ServiceNow’s Applied AI Forward Deployed Engineering team partners with strategic customers to identify valuable AI opportunities and build scalable, AI-native solutions. The team embeds in customer environments to solve mission-critical challenges, deliver outcomes quickly, and turn successful implementations into reusable patterns for the Now AI Platform and enterprise AI.

As a GenAI/ML Engineer, you will work directly with customers to turn ambiguous business problems into production-ready AI systems. You will own end-to-end solution development, including backend services, LLM pipelines, and front-end integrations. The work includes designing and deploying RAG pipelines, agentic workflows, evaluation systems, and guardrails; rapidly prototyping and iterating with users; and hardening pilots into reliable, monitored services. You will also shape technical relationships, translate between business and engineering stakeholders, and contribute reusable libraries, tooling, and patterns that influence the platform roadmap.

Requirements

• Experience leveraging or critically evaluating how to integrate AI into work processes, decision-making, or problem-solving.
• At least 8 years of software engineering experience, including at least 2 years building systems in customer-facing or embedded roles.
• Experience building machine learning or GenAI systems using technologies such as LLMs, embeddings, vector databases, and RAG architectures.
• Demonstrated ability to design and implement AI-native software in production environments.
• Backend engineering strength with Python, Node.js, or Java.
• Frontend engineering experience with React or Angular.
• Experience with REST or GraphQL APIs.
• Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management.
• Ability to debug distributed systems, tune for latency, and implement monitoring.
• Ability to contribute to shared SDKs and tools that improve engineering velocity.
• Product sensibility, including prioritizing user value, MVP iteration, and long-term scale.
• DevOps experience deploying in AWS, Azure, or GCP using CI/CD, containers, and infrastructure as code.
• Able to travel up to 30% to work onsite with customers.

Nice To Haves

• Experience integrating AI into SaaS platforms such as ServiceNow or Salesforce.
• Track record of production deployments in secure, regulated enterprise environments.
• Contributions to developer experience tooling, frameworks, or reusable AI scaffolds.

Responsibilities

• Partner directly with customers to discover problems and frame high-impact AI use cases.
• Design and build end-to-end GenAI and machine learning systems, including RAG pipelines, agentic workflows, evaluation, and guardrails, and deploy them to production.
• Prototype quickly, iterate with real users, and harden pilots into reliable, monitored services.
• Own the technical relationship and translate between business stakeholders and engineering teams.
• Raise the bar for machine learning depth and engineering quality across the team.
• Author reusable libraries, prompts, and scaffolds that support multiple deployments and projects.
• Contribute to internal tooling and platform capabilities, informing the platform roadmap.
• Lead implementation from initial concept through production delivery in customer environments.

Benefits

• Health plans
• Flexible spending accounts
• 401(k) plan with company match
• Employee stock purchase plan
• Matching donations
• Flexible time away plan
• Family leave programs
• Equity, when applicable
• Variable or incentive compensation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed