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.

Responsibilities

• Collaborer avec les clients pour concevoir, mettre en œuvre et livrer des solutions prêtes à l'emploi.
• Développer des applications activées par LLM qui couvrent la logique backend, l'orchestration des données et l'interface utilisateur frontale.
• Codifier des actifs réutilisables, tels que des bibliothèques, des invites et des échafaudages, pour accélérer les engagements futurs.
• LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
• Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
• Machine Learning: Foundations of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQL

Requirements

• System architecture: Proven ability to design and implement AI-native software in production environments
• Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
• 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
• Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
• Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
• DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
• 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