Forward Deployed Solution Engineer (Applied AI FDE)

Join our team as a Forward Deployed Solution Engineer (Applied AI FDE). In this role, you will act as the CTO of the build, owning everything from backend services to LLM pipelines and front-end integrations. You will partner with customers in the field to design, implement, and deliver solution-ready builds in agile sprints. Your software will become the reference implementation for scalable GenAI in the enterprise. You will also codify patterns, shape internal tooling, and accelerate innovation.

- Act as the CTO of the build, owning everything from backend services to LLM pipelines and front-end integrations. - Partner with customers to design, implement, and deliver solution-ready builds in agile sprints, ensuring production-grade delivery. - Codify reusable assets—libraries, prompts, scaffolds—to accelerate future engagements and shape developer experience.

- 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 embed deeply with customer teams, diagnose root problems, and architect AI-powered workflows that run at scale - You think like a product-minded CTO, balancing creativity with pragmatism to deliver impact - You don’t just debug code—you debug systems, context, and customer pain points - DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code - System architecture: Proven ability to design and implement AI-native software in production environments - Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org - 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 - 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 - Product sensibility: Prioritize for user value, MVP iteration, and long-term scale - Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters - Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL) - Relevant Experience: 10+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles - 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