Forward Deployed Solution Engineer – Applied AI FDE

Description

The company's Applied AI Forward Deployed Engineering team works with its largest strategic customers to shape how enterprises use AI. The team finds high-value opportunities, speeds up business results, and builds reusable AI-native solutions for the company's platform.

The team embeds in customers' real operating environments to solve their most critical problems with scalable AI solutions. Work that succeeds is turned into patterns that help other platform users and enterprises.

Enterprises now expect AI projects to produce measurable business value, not only potential. The role turns advanced LLM capabilities into resilient, secure, and scalable software.

This is a Forward Deployed Solution Engineer (FDSE) role. You own the technical direction of each build, from backend services and LLM pipelines to front-end integrations. You work with customers on site to design, implement, and deliver solution-ready builds in agile sprints. Your code becomes the reference implementation for scalable enterprise GenAI, and it must hold up in production across industries.

Responsibilities

• Build solution-ready LLM-enabled applications covering backend logic, data orchestration, and the front-end UI
• Work on site alongside customers to adapt, deploy, and improve solutions in live environments
• Turn libraries, prompts, and scaffolds into reusable assets that speed up future engagements
• Send field feedback to platform and product teams to improve the developer experience
• Deliver production-ready solutions through agile end-to-end sprints
• Work across APIs, orchestration pipelines, vector databases, LLM frameworks, and UI components
• Integrate with legacy systems, handle unclear requirements, and ship safely and quickly
• Build scaffolds, SDKs, and documentation so successful patterns can be reused across customers
• Feed field-tested insights and extensible code into product strategy

Requirements

• You are a systems-minded, AI-native engineer who ships working software and can own the full stack, from elegant APIs and intuitive UIs to scalable orchestration pipelines
• You think like a product-minded CTO, balancing creativity with practical delivery
• You work closely with customer teams, find root causes, and design AI-powered workflows that run at scale
• You debug systems, surrounding context, and customer pain points, not only code
• You have used AI in your work, such as in processes, decision-making, problem-solving, or automation, or you have analyzed how AI could change a function or industry
• You have 10+ years of software engineering experience, including 2+ years building systems in customer-facing or embedded roles
• You have designed and shipped AI-native software in production
• You are strong in backend (Python, Node.js, Java), frontend (React, Angular), and APIs (REST, GraphQL)
• You have a solid foundation in tools such as MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, and SQL
• You are familiar with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
• You have debugged distributed systems, tuned for latency, and set up monitoring
• You contribute to shared SDKs and tools that speed up the whole engineering organization
• You prioritize user value, iterate on MVPs, and design for long-term scale
• You have deployed on AWS, Azure, or GCP using CI/CD, containers, and infrastructure as code
• You can travel up to 30% to work onsite with customers
• Preferred: You have integrated AI into SaaS platforms such as the company or Salesforce
• Preferred: You have deployed to production in secure, regulated enterprise environments
• Preferred: You have contributed to developer experience tooling, frameworks, or reusable AI scaffolds

Conditions

Travel of up to 30% is required to work onsite with customers

Work personas (flexible, remote, or required in office) are assigned based on the nature of the work and the assigned work location

The company may use a third-party service to check the distance between your primary residence and the nearest company office when determining work persona eligibility