Forward Deployed Solution Engineer – Applied AI FDE in London

Forward Deployed Solution Engineer – Applied AI FDE in London

London Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
ServiceNow, Inc.

At a Glance

  • Tasks: Build innovative AI solutions and collaborate with customers to solve real-world challenges.
  • Company: Join ServiceNow, a leader in AI-driven business transformation.
  • Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic work environment with a strong emphasis on collaboration and innovation.
  • Why this job: Make a tangible impact by developing cutting-edge AI applications that drive enterprise success.
  • Qualifications: 10+ years in software engineering with a focus on AI integration and customer-facing roles.

The predicted salary is between 70000 - 90000 £ per year.

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.

Team Bio

ServiceNow’s Applied AI Forward Deployed Engineering (FDE) team is where bold ideas meet transformative action. We partner with our most strategic customers to shape the future of enterprise AI. Together, we identify high-value opportunities, accelerate business outcomes, and build reusable AI-native solutions that advance the Now AI Platform.

Our mission:

We partner deeply with our customers to build intelligent, scalable AI solutions that solve their most mission‑critical challenges. By embedding in real‑world complexity, we deliver fast, iterate with purpose, and transform every success into reusable patterns that accelerate transformation across the Now Platform and the broader enterprise.

Why This Role Matters

Enterprises are raising the bar. AI initiatives must deliver business value—not just promise potential. That means taking cutting‑edge LLM capabilities and turning them into resilient, secure, and scalable software.

As a Senior Forward Deployed Software Engineer (FDSE), you act as the CTO of the build—owning everything from backend services to LLM pipelines and front‑end integrations. You partner with customers in the field to design, implement, and deliver solution‑ready builds in agile sprints. Your software becomes the reference implementation for scalable GenAI in the enterprise. You codify patterns, shape internal tooling, and accelerate innovation—delivering systems that are battle‑tested in production and scalable across industries.

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).

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: Prioritise 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.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, 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 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.

Forward Deployed Solution Engineer – Applied AI FDE in London employer: ServiceNow, Inc.

At ServiceNow, we foster an innovative and collaborative work culture that empowers our employees to drive meaningful change through AI technology. As a Forward Deployed Solution Engineer, you will have the opportunity to work closely with strategic customers, shaping the future of enterprise AI while enjoying a flexible work environment that promotes personal growth and professional development. With a commitment to diversity and inclusion, we ensure that every voice is heard and valued, making ServiceNow an exceptional place to build your career.

ServiceNow, Inc.

Contact Details:

ServiceNow, Inc. Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Forward Deployed Solution Engineer – Applied AI FDE in London

Join Local Tech Meetups

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Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ServiceNow, Inc..

Tap into Online Developer Communities

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We think you need these skills to ace Forward Deployed Solution Engineer – Applied AI FDE in London

AI-Native Engineering
Full Stack Development
Backend Services (Python, Node.js, Java)
Frontend Development (React, Angular)
API Development (REST/GraphQL)
LLM Tooling (LangChain, Semantic Kernel)
Data Orchestration

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ServiceNow, Inc..

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ServiceNow, Inc. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at ServiceNow, Inc.

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ServiceNow, Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.