Applied AI Engineer

About Unframe

Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.

With over $100M in TCV secured within 12 months, and a new $50M Series B led by Highland Europe, Unframe is rapidly scaling globally alongside Fortune 500 customers, backed by Bessemer, Craft, and TLV.

What You'll Do

As an Applied AI Engineer, you’ll work closely with customers and internal teams to translate business problems into AI-driven solutions. You’ll be hands-on with AI workflows, and help bridge the gap between model capabilities and real-world impact.

About The Role

• Implement workflows and configure model behavior for customer solutions.
• Build integrations between AI logic and deterministic building blocks.
• Work with platform and research teams to surface platform-level improvements.
  
  

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 4+ years of experience in software engineering, data science, machine learning, or research roles (including relevant academic experience).
• Experience building and delivering production solutions to customers using Python, TypeScript, or similar.
• Experience building pipelines for structured and unstructured data, including work with vector databases and retrieval-augmented generation (RAG)-like architectures.
• Experience with prompt design, evaluation, and iteration workflows.
• Ability to rapidly understand complex domains and read and implement research papers.
• Comfortable working with real-time applications and production systems.
  
  

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, Google ADK) and patterns such as ReAct, self-reflection, and hierarchical delegation.
• Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Background in data pipelines, APIs, or system integrations.
• Experience working with enterprise or B2B customers.
• Experience working in fast-paced startup environments.
  
  

• Real ownership from day one. Drive decisions, shape ideas and make them work.
• Your fastest learning years. Build alongside founders and VPs in a space that moves weekly.
• You'll have the opportunity to write and build what comes next.