Forward Deployed Solution Engineer – Applied AI FDE
ServiceNow7 days ago
Responsibilities
- Build and deliver production-ready LLM-enabled applications across backend logic, data orchestration, and frontend UI.
- Embed with customers to diagnose problems, integrate with legacy systems, deploy solutions, and iterate in live environments.
- Implement APIs, orchestration pipelines, vector database integrations, LLM frameworks, and UI components.
- Create reusable libraries, prompts, scaffolds, SDKs, and documentation for future deployments.
- Define evaluation metrics and build evaluation, monitoring, tracing, and quality telemetry systems for AI applications.
- Implement responsible AI protections including guardrails, PII handling, redaction, prompt-injection mitigation, jailbreak mitigation, and output validation.
- Provide field-tested feedback to platform and product teams and influence internal tooling and product strategy.
- Lead implementation from zero to one while collaborating with architects, product managers, and customer stakeholders.
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, from data preparation through monitoring and iteration.
- Hands-on experience with retrieval-augmented generation, embeddings, vector databases, prompt engineering, structured outputs, function or tool calling, context management, and agentic workflows.
- Experience with AI evaluation methods including golden datasets, offline evaluations, LLM-as-judge, A/B testing, and human-in-the-loop feedback.
- Working knowledge of supervised learning, embeddings, transformers, attention, tokenization, context windows, and quantization.
- Experience with LangChain or LangGraph, LlamaIndex, Semantic Kernel, PyTorch, TensorFlow, scikit-learn, Hugging Face, and major model APIs or platforms.
- Strong backend skills in Python, Node.js, or Java; frontend skills in React or Angular; and experience with REST or GraphQL APIs.
- Ability to design and implement AI-native production software and debug distributed systems while optimizing latency and throughput.
- Experience with monitoring, token and cost tracking, tracing, span-level debugging, and AI quality telemetry.
- Experience deploying to AWS, Azure, or GCP with containers, infrastructure-as-code, CI/CD, model and prompt versioning, automated evaluation gates, and safe rollout patterns.
- Experience implementing data governance and responsible AI controls in customer environments.
- Ability to contribute to shared SDKs and tools, prioritize user value, iterate on MVPs, and operate effectively in ambiguous field environments.
- Ability to travel up to 30% and work directly with customer teams.
- Preferred: experience integrating AI into ServiceNow or Salesforce, fine-tuning with LoRA or PEFT, inference optimization, self-hosted model serving, ML data pipelines, feature stores, streaming ingestion, regulated environments, and customer-facing technical workshops.
Benefits
- Regular employee position with a flexible or remote work persona in the EMEA region.
- Distributed-work flexibility is based on the assigned work location and role requirements.
- Up to 30% travel may be required for onsite customer engagements.
Tech Stack
Categories
Forward Deployed
About ServiceNow
ServiceNow (NYSE: NOW) makes the world work better for everyone. Our cloud-based platform and solutions help digitize and unify organizations so that they can find smarter, faster, better ways to make work flow. So employees and customers can be more connected, more innovative, and more agile. And we can all create the future we imagine. The world works with ServiceNow. For more information, visit www.servicenow.com.