Forward Deployed Solution Engineer – Applied AI FDE

Description

The Applied AI Forward Deployed Engineering team at the company 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.

Enterprises now expect AI projects to produce measurable business value, not just potential. That means turning advanced LLM capabilities into resilient, secure, scalable software.

As a Forward Deployed Solution Engineer, you act as the CTO of each build. You own the work from backend services and LLM pipelines to front-end integrations. You work with customers in the field to design, implement, and deliver solutions that are ready to use, in agile sprints. Your software becomes the reference implementation for scalable GenAI in the enterprise, and it is proven in production across industries.

Responsibilities

• Build LLM-enabled applications that are ready for customers, covering backend logic, data orchestration, and the 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.
• Build with flexibility across APIs, orchestration pipelines, vector databases, LLM frameworks, and UI components.
• Move quickly in unclear situations, including integrating with legacy systems, while keeping releases safe.
• Create reusable libraries, prompts, scaffolds, SDKs, and documentation so that successful work can scale across customers.
• Share field feedback with platform and product teams to improve developer experience and inform product strategy.
• Success means your builds reach production at scale, your libraries and prompts are reused across several deployments, your work shapes internal tooling and the platform roadmap, and you lead implementations from zero to one with the trust of architects, PMs, and customer teams.

Requirements

• You are a systems-minded AI-native engineer who ships working software. You can own the full stack and care equally about clean APIs, usable UIs, and scalable pipelines. You think like a product-minded CTO and balance creativity with pragmatism.
• You work closely with customer teams, find root causes, and design AI-powered workflows that run at scale. You debug systems, context, and customer problems, not only code.
• You have used AI in your work, such as in tools, workflow automation, decision-making, or problem-solving, or you have critically assessed its impact on a role 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 implemented AI-native software that runs in production.
• You have strong skills in backend development with Python, Node.js, or Java, in frontend development with React or Angular, and in REST or GraphQL APIs.
• You understand ML and data 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 can debug distributed systems, tune for latency, and set up monitoring.
• You contribute to shared SDKs and tools that speed up engineering across the organisation.
• You prioritise 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% of the time to work onsite with customers.
• Preferred: experience integrating AI into SaaS platforms such as Salesforce or the company's platform.
• Preferred: a track record of production deployments in secure, regulated enterprise environments.
• Preferred: contributions 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 role and the work location.

To check eligibility for a work persona, the company may measure the distance between your main residence and the nearest company office using a third-party service.