Applied AI Engineer

About Us

At Unframe, we build AI-powered products that address real-world challenges. Our platform team is at the core of this mission, developing the infrastructure, reusable components, and internal tools that enable rapid and reliable product delivery. We work on-site from our Tel Aviv office, collaborating closely across engineering, product, and AI to move fast and build with purpose.

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.

Responsibilities

• 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.

Requirements

• 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.

Nice to Have

• 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.