Forward Deployed Solution Engineer – Applied AI FDE

Description

The Applied AI Forward Deployed Engineering team works with the company's 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 Now AI Platform.

The work centres on turning recent LLM capabilities into software that is resilient, secure and scalable, so AI projects produce measurable business value rather than only promise. Solutions built in the field become reference implementations and reusable patterns for the wider platform.

The role is titled Forward Deployed Software Engineer (FDSE) and is also listed as Forward Deployed Solution Engineer, Applied AI FDE.

Responsibilities

• Build ready-to-deploy LLM-enabled applications covering backend logic, data orchestration and front-end UI.
• Work on site beside customers to adapt, deploy and refine solutions in live environments.
• Deliver production-ready solutions through agile sprints from start to finish.
• Use a broad toolset, including APIs, orchestration pipelines, vector databases, LLM frameworks and UI components.
• Integrate with legacy systems, handle unclear requirements and ship safely at pace.
• Turn solutions into reusable assets such as libraries, prompts, scaffolds, SDKs and documentation for future projects.
• Share field feedback with platform and product teams to improve the developer experience and product direction.

Requirements

• Be a systems-minded, AI-native engineer who ships working software and can own the full stack, from APIs and orchestration to UIs.
• Balance creative design with practical delivery, thinking about product value as well as engineering.
• Embed with customer teams, find root causes, and design AI-powered workflows that run at scale. Look past the code to the system, the context and the customer's problems.
• Experience using or critically assessing AI in work processes, decisions or problem solving, such as AI tools, workflow automation or analysis of AI-driven insights.
• 10+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles.
• Proven record designing and shipping AI-native software in production.
• Strong backend skills in Python, Node.js or Java, frontend skills in React or Angular, and API experience with REST or GraphQL.
• Working knowledge of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark or SQL.
• Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search and context management.
• Experience debugging distributed systems, tuning latency and setting up monitoring.
• Able to contribute to shared SDKs and tools that speed up the whole engineering organisation.
• Prioritise user value, iterate on MVPs and plan for long-term scale.
• Experience deploying on AWS, Azure or GCP using CI/CD, containers and infrastructure as code.
• Able to travel up to 30% to work onsite with customers.
• Preferred: experience integrating AI into SaaS platforms such as the company or Salesforce.
• Preferred: production deployments in secure, regulated enterprise environments.
• Preferred: contributions to developer experience tooling, frameworks or reusable AI scaffolds.

Conditions

Work persona (flexible, remote or required in office) is assigned by the nature of the role and the employee's work location.

The company may check the distance between your home and the nearest office with a third-party service to confirm eligibility for a work persona.