Required Sr. Principal AI Researcher, AI Transformation
Job Summary
Shape the future of AI-powered software engineering. As part of our AI Transformation group, youll join a multidisciplinary group building state-of-the-art, agentic AI systems that directly elevate the productivity of thousands of internal engineers.
We build internal AI infrastructure, frameworks, agents, harnesses, methodologies, and adoption programs powered by cutting-edge LLMs. Whether you are researching novel AI paradigms, architecting platform infrastructure, engineering end-to-end agentic tools, or driving developer enablement, your work will redefine how software gets built at scale.
This is an applied AI research role, where you will be inventing new technology, bringing the latest innovations into our agentic software development practices, and responsible for co-building systems that get deployed to our entire, global Cortex engineering organization.
Key Responsibilities:
Stay at the forefront of AI advancements in agentic coding and integrate state-of-the-art techniques.
Build functional Proof of Concepts (PoCs) and architectural skeletons to evaluate new AI techniques before scaling.
Critically audit and challenge internal AI solutions, benchmarks, and architectures to prevent technological obsolescence.
Design rigorous testing methodologies to assess model accuracy, latency, cost efficiency, and drift across solutions.
Research and design advanced knowledge-retrieval architectures, including standard and graph-based RAG and hybrid contextual search.
Collaborate with core AI engineering to transition validated prototypes into reusable components for our engineering workforce.
Coordinate closely with the US Foundational AI Research team via flexible evening Israel / morning US meetings.
Requirements: Required Qualifications:
Minimum of 5 years of experience in Applied AI research, Data Science, or Machine Learning engineering.
Deep, hands-on experience over the past 12+ months developing leading-edge agentic coding practices.
Proficiency in Python and/or Typescript, with deep familiarity in Agentic AI orchestration libraries like LangChain, LlamaIndex, or LangGraph.
Experience with automated statistical evaluation to track model drift, latency, costs, and hallucination rates.
Hands-on experience developing advanced RAG pipelines, GraphRAG frameworks, and interacting with Graph Databases or vector indices.
Practical experience with autonomous agent protocols, multi-agent communication layers, or Model Context Protocol (MCP).
Preferred Qualifications:
Understanding of secure data pipelines, including Role-Based Access Control (RBAC) and prompt injection mitigation.
Hands-on production experience utilizing Google Cloud Platform (GCP) services and infrastructure.
Strong knowledge of data privacy and security considerations specific to AI and ML systems.
Post-graduate work or equivalent advanced degree in Artificial Intelligence, Data Science, or a related field.
This position is open to all candidates.