AI Engineer

Cellebrite

. Design and maintain a LangGraph-based Agent Harness optimized for online and offline/on-premise deployment .

Posted 9/17/2026full-timePetah Tikva • IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python development and agent orchestration frameworks, particularly LangGraph, while ensuring high-quality AI solutions through rigorous evaluation and testing processes. Proficient in building scalable applications with a focus on observability and performance across AI workloads.

Highest-signal resume keywords

Python DevelopmentLangGraph FrameworkAI Evaluation FrameworksAgentic AI ArchitectureEnterprise-Scale Application Development

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Hard Skills

Software DevelopmentAgent OrchestrationRAG PipelinesVector DatabasesEmbeddingsRetrieval TechniquesPrompt TestingQuality MeasurementOOP Language ProficiencyTelemetry Implementation

Soft Skills

Attention to DetailMultitaskingInterpersonal Skills

Tools & Technologies

MCPA2AForensic EnginesSaaS Environment

Certifications & Qualifications

Bachelor's Degree in Computer Science

Industry Keywords

AI ModelsProduction-Grade SystemsAutomated Regression TestingBenchmarking FrameworksFeedback Loops

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design and maintain a LangGraph-based Agent Harness optimized for online and offline/on-premise deployment
Use hybrid LLM and deterministic layers to balance speed, memory, and costs
Own the complete evaluation lifecycle, including datasets, benchmarking frameworks, and automated regression testing
Ensure output accuracy through evaluation and regression testing
Standardize tool-calling interfaces for forensic engines
Collaborate with researchers to operationalize AI models into Cellebrite's products
Build, evaluate, and iterate on AI and agentic solutions across the software lifecycle, from rapid prototypes and POCs to production-grade systems
Implement solid design, flexible implementation, strong telemetry, and production feedback loops

Requirements

What you’ll need

Bachelor's degree in computer science or an engineering-related field
6+ years of experience in software development
Proven experience as a Python developer
Experience with agent orchestration frameworks such as LangGraph
Experience with Agentic AI architecture, MCP, and A2A
Solid understanding of RAG pipelines, vector databases, embeddings, and retrieval techniques including chunking, indexing, filtering, and relevance tuning
Experience with AI evaluation frameworks, prompt testing, or offline/online quality measurement
Attention to detail, ability to multitask, and strong interpersonal skills
Preferred: experience in enterprise-scale application development in a SaaS environment
Preferred: strong observability design across infrastructure and AI workloads, including metrics, logging, tracing, and AI quality signals
Preferred: experience with an OOP language

Benefits

Comp & perks

Remote/hybrid work arrangement
Online, offline, and on-premise deployment experience
Work with leading LLMs and the broader agentic ecosystem
Cutting-edge frameworks and techniques
Production feedback loops and telemetry-driven development