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.

You own the full stack—and are equally motivated by elegant APIs, intuitive UIs, and scalable orchestration pipelines

Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters

USD 201,300 - 352,300

Responsibilities

• 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 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

Requirements

• 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
• 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
• Track record of production deployments in secure, regulated enterprise environments

Preferred

• Experience integrating AI into SaaS platforms like ServiceNow or Salesforce
• Contributions to dev experience tooling, frameworks, or reusable AI scaffolds