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Forward Deployed Solution Engineer – Applied AI FDE
ServiceNow
London, GBR
Full-time
Senior · 10+ years experience
Remote
Discovered 4 days ago
airflowangularawsazuregcpgraphql
Key Skills for This Role
airflowangularawsazuregcpgraphql
Full Job Posting
Who You Are:
- You are a systems-minded, AI-native engineer who ships real software. You own the full stack—and are equally motivated by elegant APIs, intuitive UIs, and scalable orchestration pipelines. You think like a product-minded CTO, balancing creativity with pragmatism to deliver impact.
- You embed deeply with customer teams, diagnose root problems, and architect AI-powered workflows that run at scale. You don’t just debug code—you debug systems, context, and customer pain points.
- You will:
- Build solution-ready LLM-enabled applications that span backend logic, data orchestration, and front-end UI
- Operate in the field, working side-by-side with customers to adapt, deploy, and iterate in live environments
- Codify reusable assets—libraries, prompts, scaffolds—to accelerate future engagements
- Shape developer experience by sharing feedback with platform and product teams
- What You’ll Do:
- Deliver Production - ready solution in agile end-to-end sprints
- Engineer with versatility: APIs, orchestration pipelines, vector DBs, LLM frameworks, UI components
- Operate with agility: integrate with legacy systems, navigate ambiguity, ship safely at speed
- Codify patterns: build scaffolds, SDKs, and documentation to scale success across customers
- Influence platform: inform product strategy through field-tested insights and extensible code
- What Success Looks Like:
- Production-grade delivery: Your solution builds consistently convert to scaled deployments in production environments
- Reusable impact: You author libraries, prompts, and scaffolds that power multiple deployments and projects
- Platform influence: Your work shapes internal tooling and is integrated into platform roadmap and primitives
- Velocity and precision: You move fast without breaking things—shaping resilient, secure systems in high-stakes contexts
- Engineering leadership: You are trusted by architects, PMs, and customer teams to lead implementation from zero to one
- Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
- Relevant Experience: 10+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
- System architecture: Proven ability to design and implement AI-native software in production environments
- Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
- Machine Learning: Foundations of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQL
- LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
- Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
- Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
- Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
- DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
- Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
- Experience integrating AI into SaaS platforms like ServiceNow or Salesforce
- Track record of production deployments in secure, regulated enterprise environments
- Contributions to dev experience tooling, frameworks, or reusable AI scaffolds
What You Bring:
- Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
- Relevant Experience: 10+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
- System architecture: Proven ability to design and implement AI-native software in production environments
- Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
- Machine Learning: Foundations of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQL
- LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
- Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
- Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
- Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
- DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
- Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
Preferred Qualifications:
- Experience integrating AI into SaaS platforms like ServiceNow or Salesforce
- Track record of production deployments in secure, regulated enterprise environments
- Contributions to dev experience tooling, frameworks, or reusable AI scaffolds
- Work Personas
- We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
- Equal Opportunity Employer
- ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
- Accommodations
- We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance.
- Export Control Regulations
- For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
- From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
- It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
- Join us to put AI to work for people.
Responsibilities
- Deliver Production - ready solution in agile end-to-end sprints
- Engineer with versatility: APIs, orchestration pipelines, vector DBs, LLM frameworks, UI components
- Operate with agility: integrate with legacy systems, navigate ambiguity, ship safely at speed
- Codify patterns: build scaffolds, SDKs, and documentation to scale success across customers
- Influence platform: inform product strategy through field-tested insights and extensible code
- Production-grade delivery: Your solution builds consistently convert to scaled deployments in production environments
- Reusable impact: You author libraries, prompts, and scaffolds that power multiple deployments and projects
- Platform influence: Your work shapes internal tooling and is integrated into platform roadmap and primitives
- Velocity and precision: You move fast without breaking things—shaping resilient, secure systems in high-stakes contexts
- Engineering leadership: You are trusted by architects, PMs, and customer teams to lead implementation from zero to one
About ServiceNow
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