Forward Deployed Solution Engineer – Applied AI FDE
ServiceNow4 hours ago
Montréal, CanadaSenior
Responsibilities
- Lead customer discovery workshops and identify high-impact AI use cases.
- Design and build production-ready GenAI/ML systems using LLMs, RAG, retrieval, and workflow orchestration.
- Prototype with real users, iterate quickly, and harden pilots into reliable monitored services.
- Own the technical relationship between customer stakeholders and engineering teams.
- Collaborate with Forward Deployed Software Engineers to build, test, and iterate solutions.
- Create reusable frameworks, templates, modular components, documentation, and technical onboarding assets.
- Define evaluation metrics and improve AI system quality, reliability, and scalability.
- Capture deployment feedback to influence product strategy and platform priorities.
- Deliver validated AI solution builds within 8–12 weeks and enable scaled production deployment.
- Travel up to 30% to work onsite with customers.
Requirements
- 8+ years of software engineering experience, including 2+ years building and shipping systems in customer-facing or embedded roles.
- 3+ years of experience building and deploying production ML or AI systems end to end.
- Hands-on experience with RAG, embeddings, vector databases, prompt engineering, structured outputs, tool calling, context management, and agentic workflows.
- Experience building evaluation harnesses using golden datasets, offline evaluations, LLM-as-judge, A/B testing, and human-in-the-loop feedback.
- Working knowledge of supervised learning, deep learning, transformers, attention, tokenization, context windows, and quantization.
- Experience with LangChain/LangGraph, LlamaIndex, Semantic Kernel, PyTorch, TensorFlow, scikit-learn, Hugging Face, and major model APIs or platforms.
- Strong software engineering experience with Python, Node.js, Java, React, Angular, REST, and GraphQL.
- Ability to design and implement AI-native software in production environments.
- Experience debugging distributed systems, optimizing latency and throughput, and implementing monitoring and quality telemetry.
- Experience with LangSmith, Arize, Weights & Biases, and OpenTelemetry for tracing and observability.
- Experience deploying on AWS, Azure, or GCP with containers, infrastructure-as-code, and CI/CD.
- Experience with model and prompt versioning, automated evaluation gates, canary deployments, shadow deployments, and feature flags.
- Practical experience with AI guardrails, PII handling and redaction, prompt-injection and jailbreak mitigation, output validation, and data governance.
- Ability to contribute to shared SDKs and tools and to prioritize user value, MVP iteration, and long-term scale.
- Preferred experience includes ServiceNow or Salesforce AI integrations, LoRA/PEFT, distillation, vLLM, TensorRT-LLM, Triton, GPU optimization, feature stores, streaming ingestion, large-scale document processing, and regulated environments.
- Comfort leading technical workshops, discovery sessions, and architecture reviews with customer stakeholders.
Benefits
- Flexible work persona within ServiceNow’s distributed work model.
- Regular employee position in the North America and Canada region.
- Travel of up to 30% for onsite customer delivery.
Tech Stack
Categories
Forward Deployed
About ServiceNow
ServiceNow builds a cloud platform for enterprise digital workflows, covering IT service management, customer service, HR service delivery, security operations, and operations management, plus tools for custom app development. It sells subscription SaaS to large organizations and public-sector agencies to automate processes and connect data across systems. Founded in 2004 and headquartered in Santa Clara, California, ServiceNow is a public company listed on the NYSE under the ticker NOW.