Forward Deployed Solution Engineer – Applied AI

This is a fully remote position, open to applicants in Netherlands.

📋 Description

• Develop solution-ready applications powered by LLM, encompassing backend logic, data orchestration, and front-end user interface.

• Collaborate closely with customers in real-time to adapt, deploy, and iterate within live environments.

• Provide production-ready solutions through agile, comprehensive sprints.

• Design and engineer APIs, orchestration pipelines, vector databases, LLM frameworks, and user interface components.

• Integrate with legacy systems, manage ambiguity, and deliver safely at speed.

• Create scaffolding, SDKs, libraries, prompts, and documentation to enhance customer success.

• Influence developer experience by providing feedback to platform and product teams.

• Troubleshoot distributed systems, optimize latency, and set up monitoring.

• Deploy systems leveraging cloud platforms, CI/CD practices, containers, and infrastructure-as-code.

• Contribute to product strategy with insights gained from field experiences and extensible code.

• Oversee implementations from conception to completion in collaboration with architects, product managers, and customer teams.

⛳️ Requirements

• Over 10 years of experience in software engineering.

• More than 2 years of experience building systems in customer-facing or embedded roles.

• Proven experience in leveraging or critically assessing the integration of AI in work processes, decision-making, or problem-solving.

• Demonstrated ability to design and implement AI-native software in production environments.

• Backend expertise in Python, Node.js, and Java.

• Frontend proficiency with React and Angular.

• Familiarity with REST and GraphQL APIs.

• Knowledge of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, and SQL.

• Understanding of LangChain, Semantic Kernel, prompt chaining, vector search, and context management.

• Skills in debugging distributed systems, optimizing latency, and implementing monitoring solutions.

• Capability to contribute to shared SDKs and tools.

• Product sensibility with a focus on user value, MVP iteration, and long-term scalability.

• Experience with deployments in AWS, Azure, or GCP utilizing CI/CD, containers, and infrastructure-as-code.

• Willingness to travel up to 30% and work onsite as necessary.

• Preferred: Experience in integrating AI into SaaS platforms such as ServiceNow or Salesforce.

• Preferred: Experience with production deployments in secure, regulated enterprise environments.

• Preferred: Contributions to developer-experience tooling, frameworks, or reusable AI scaffolds.

🏝️ Benefits

• Flexible or remote work arrangements.

• Option for remote work.

• Commitment to equal opportunity employment.

• Support for reasonable accommodations.