Full-Time Director, Forward Deployed Solution Engineer – Applied AI
ServiceNow is hiring a remote Full-Time Director, Forward Deployed Solution Engineer – Applied AI. The career level for this job opening is Manager and is accepting Dublin, Ireland based applicants remotely. Read complete job description before applying.
ServiceNow
Job Title
Posted
Career Level
Career Level
Locations Accepted
Share
Job Details
Why This Role Matters: As a Director, Forward Deployed Software Engineer (FDSE), you lead high-performing engineering teams embedded with customers to deliver production-ready GenAI solutions. You provide technical direction, unblock delivery challenges, and ensure architectural integrity across the full stack—from backend services and LLM pipelines to front-end integrations.
Who You Are: You are a strategic engineering leader with deep systems thinking and a passion for building AI-native software at scale.
You Will:
- Lead Teams Building Solution-Ready Applications
- Drive Field Execution
- Codify Reusable Engineering Assets
- Shape Developer Experience
What You’ll Do:
- Deliver End-to-End Solutions Through Teams
- Guide Versatile Engineering Practices
- Enable Agile Execution
- Scale Through Codified Patterns
- Influence Platform Strategy
What Success Looks Like:
- Production-ready delivery
- Reusable impact
- Platform influence
- Velocity and precision
- Engineering leadership
What You Bring:
- Experience: In leveraging or critically thinking about how to integrate AI into work processes
- Relevant Experience: 13+ 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-ready 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
- 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-ready deployments in secure, regulated enterprise environments
- Contributions to dev experience tooling, frameworks, or reusable AI scaffolds