The Senior Forward Deployed Software Engineer (FDSE) will join the Applied AI Forward Deployed Engineering team to partner with strategic enterprise customers, identify high-value opportunities, and deliver production-ready, LLM-enabled applications. The person in this role will operate in customer environments, lead end-to-end technical delivery across the full stack, and convert engagements into reusable patterns and assets that accelerate future deployments and inform the platform roadmap.
Responsibilities
- Build and deliver production-ready AI solutions: Own end-to-end delivery of LLM-enabled applications in agile sprints, including backend services, data orchestration, LLM pipelines, and front-end integrations. Make architecture and implementation decisions that enable scaled production deployments.
- Embed with customers in the field: Work side-by-side with strategic customer teams, often onsite (up to 30% travel). Diagnose root problems, understand context and customer pain points, identify high-value AI opportunities. Adapt, deploy, and iterate in live environments.
- Act as the “CTO of the build,” making architecture and implementation decisions.
- Engineer across the full stack: Design and implement APIs (REST/GraphQL), orchestration pipelines, vector database integrations, LLM frameworks (e.g., LangChain, Semantic Kernel), and UI components (React, Angular). Integrate with legacy systems and navigate ambiguity while delivering reliably and securely.
- Codify reusable assets: Create libraries, SDKs, prompts, scaffolds, and documentation to make successful projects repeatable across customer engagements.
- Influence platform and product: Share field-tested insights with platform and product teams to shape internal tooling and contribute to the Now AI Platform roadmap and primitives.
- Ensure performance, reliability, and security: Debug distributed systems, tune for latency, and implement monitoring and observability to deliver resilient systems for enterprise use.
- Deploy and operate in the cloud: Use AWS, Azure, or GCP with CI/CD practices, containers, and infrastructure-as-code.
- Provide engineering leadership: Lead implementations from zero to one, earn trust from architects, product managers, and customer teams, and balance rapid MVP iteration with long-term scalability.
Qualifications
- Minimum 10 years of software engineering experience, including at least 2 years in customer-facing or embedded roles.
- Proven backend development experience in one or more of: Python, Node.js, Java.
- Frontend experience with modern frameworks such as React or Angular.
- Hands-on experience with LLM tooling and patterns, including prompt chaining, vector search, and context management.
- Experience designing and implementing APIs (REST/GraphQL), orchestration pipelines, and integrations with vector databases and LLM frameworks.
- Cloud and DevOps fluency with practical knowledge of CI/CD, containers, and infrastructure-as-code on AWS, Azure, or GCP.
- Demonstrated ability to design for performance, reliability, and security in distributed systems.
- Strong communication skills and experience working directly with customer stakeholders to translate business needs into technical solutions.
- Fluent English
Benefits
- Opportunity to lead complex, high-impact AI projects with strategic enterprise customers and shape product and platform direction.
- Work that spans the full stack and advances practical, production-grade GenAI deployments and reusable engineering assets.
- Travel allowance for on-site customer engagements (up to 30% travel) and support for remote and on-site work as required by engagements.