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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 Forward Deployed Solution Engineer, you will act as the technical leader of customer engagements, owning the full stack from backend services and LLM pipelines to front-end integrations.
You will work embedded with customer teams in the field, translating high-value business opportunities into production-ready, scalable AI applications. Your responsibilities include:
- Building solution-ready LLM-enabled applications spanning backend logic, data orchestration, and UI components
- Operating in customer environments, working side-by-side with teams to adapt, deploy, and iterate in live production settings
- Designing and implementing AI-native software architectures that balance innovation with enterprise security and scalability
- Codifying reusable assets—libraries, prompt templates, scaffolds, and SDKs—to accelerate future customer engagements
- Delivering production-grade solutions in agile end-to-end sprints with velocity and precision
- Integrating with legacy systems and navigating technical ambiguity to ship safely at speed
- Shaping the ServiceNow platform roadmap by providing field-tested insights and extensible code patterns
- Influencing internal tooling and developer experience based on real-world customer feedback
Success is measured by consistent conversion of solution builds to scaled production deployments, authoring reusable libraries and scaffolds that power multiple projects, influencing platform primitives and roadmap, and earning trust from architects, product managers, and customer teams to lead implementations from zero to one.
REQUIREMENTS:
- 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, Java), frontend (React, Angular), and API design (REST/GraphQL)
- Foundations in ML tooling: MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQL
- Familiarity with LLM frameworks: LangChain, Semantic Kernel, prompt chaining, vector search, context management
- Skilled in debugging distributed systems, tuning for latency, and implementing observability/monitoring
- Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infrastructure-as-code
- Ability to travel up to 30% for onsite customer engagement
- Experience leveraging or critically thinking about AI integration into work processes, decision-making, or problem-solving
- Platform mindset with ability to contribute to shared SDKs and tools
- Product sensibility with focus on user value, MVP iteration, and long-term scale
PREFERRED QUALIFICATIONS:
- Experience integrating AI into SaaS platforms like ServiceNow or Salesforce
- Track record of production deployments in secure, regulated enterprise environments
- Contributions to developer experience tooling, frameworks, or reusable AI scaffolds
