Forward Deployed Solution Engineer – Applied AI

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

📋 Description

• Develop solution-ready applications enabled by LLM, encompassing backend logic, data orchestration, and front-end UI.

• Collaborate closely with customers on-site to adapt, deploy, and iterate within live environments.

• Deliver production-ready solutions through agile, end-to-end sprint cycles.

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

• Integrate with legacy systems and execute deployments efficiently amidst uncertainty.

• Create reusable scaffolds, SDKs, libraries, prompts, and comprehensive documentation.

• Provide feedback to platform and product teams to influence developer experience and product strategy.

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

• Lead implementations from inception to deployment alongside architects, product managers, and customer teams.

• Develop AI-native solutions for strategic clients that are scalable across various industries.

⛳️ Requirements

• Over 10 years of experience in software engineering.

• At least 2 years of experience building systems in customer-facing or embedded roles.

• Proficient in leveraging or critically assessing the integration of AI into workflows, decision-making, or problem-solving.

• Demonstrated capability to design and deploy AI-native software in production settings.

• Strong backend programming skills in Python, Node.js, and Java.

• Frontend expertise in React and Angular.

• Experience 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.

• Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management.

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

• Ability to contribute to shared SDKs and tools.

• Product sensibility focused on user value, MVP iteration, and long-term scalability.

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

• Willingness to travel up to 30% for on-site customer interactions.

• Preferred: experience with integrating AI into SaaS platforms like ServiceNow or Salesforce.

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

• Preferred: contributions to developer-experience tools, frameworks, or reusable AI scaffolds.

🏝️ Benefits

• Flexible or remote work options available.

• Reasonable accommodations provided during the application process.

• Commitment to equal opportunity employment.

• Consideration of qualified applicants with arrest or conviction records in compliance with legal requirements.