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לפני 8 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for driven and talented people like you to join our R&D team and our mission to change the future of cloud security. Ready to dive in and swim with our pod?
As a Senior Software Engineer - AI , youll design, build, and own production grade AI agents that operate at the core of cloud security platform. Youll work on distributed, cloud native services that embed agentic AI workflows into existing microservices architecture.
This role goes beyond building AI logic: youll be responsible for operating AI systems in production, ensuring they are observable, reliable, and continuously improving through systematic evaluation and data driven iteration.
On a typical day youll:
Design and implement cloud-native, distributed services that power AI-driven security features
Build and maintain agentic AI systems that reason over large-scale cloud security data and interact with multiple internal services
Own AI agents in production, including deployment, monitoring, troubleshooting, and performance optimization
Implement observability for AI systems, including metrics, logging, tracing, and alerting for agent behavior, quality, latency, and cost
Develop continuous evaluation pipelines for agentic solutions, including offline testing, regression detection, and production feedback loops
Design and optimize RAG pipelines that operate reliably over high-volume, high-variance security data
Apply strong software engineering practices: clear APIs, clean abstractions, robust error handling, and scalable data flows
Lead services end to end - from design and implementation to deployment and long-term operation
Collaborate closely with Data Platform, Product, and Security Research teams to ensure AI behavior is correct, explainable, and trustworthy
Requirements:
5+ years of professional software engineering experience building and operating production systems
Strong proficiency in Python & Typescript and experience designing backend services
Solid experience building cloud-native, distributed systems in a microservices architecture
Hands-on experience building, deploying, and maintaining AI systems in production
Proven hands-on experience building AI systems using LLM and agentic frameworks in production
Practical experience with agentic AI workflows, including tool use, multi-step reasoning, and orchestration
Experience implementing observability and monitoring for complex systems (metrics, logs, traces)
Experience designing or working with evaluation frameworks for AI systems (quality, drift, latency, cost)
Ability to reason about tradeoffs and continuously improve systems based on real-world data
Big advantage:
Experience evaluating AI systems in high-stakes domains (security, reliability, correctness)
Background in cloud security, cybersecurity, or large-scale SaaS platforms
Familiarity with RAG evaluation techniques, prompt versioning, and regression testing
Experience operating AI-enabled services at scale in AWS or similar cloud environments
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI , covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 3-4 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Requirements:
8+ years of backend engineering experience, with strong system design and platform-building expertise. Tech leadership or team leading experience is an advantage.
Strong analytical and problem-solving skills, with the ability to debug and resolve complex technical issues efficiently.
Hands-on experience with agentic systems and frameworks such as LangChain, LangSmith, ADK, or equivalent agent orchestration platforms.
Strong understanding of AI evaluation methodologies, including agent evaluations, prompt evaluation, regression testing, and quality monitoring.
High proficiency in Python for building production-grade AI frameworks and services.
Familiarity with Java and experience integrating backend platforms or tooling into Java-based systems.
Experience building observability, monitoring, or platform tooling for distributed systems.
Strong analytical skills and the ability to reason about complex, evolving AI-driven systems.
Experience with cloud platforms and scalable microservices architectures.
Excellent communication skills and a strong platform mindset, with experience enabling multiple teams.
This position is open to all candidates.
 
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09/04/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Required Senior AI Engineer - Applied AI Engineering Group
The Dream Job
It starts with you - an engineer driven to build the agentic AI platform that turns LLMs into reliable, production-grade capabilities. You care about clean APIs, well-defined service boundaries, and systems that teams can build on with confidence. Dream is AI-first across the board - every team builds and operates agents. You'll architect and ship the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation pipelines, tool-calling infrastructure, and retrieval systems. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments.
If you want to make a meaningful impact, join our mission and build the agentic AI platform that drives Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.
דרישות:
5+ years in backend or distributed systems engineering, with 2+ years focused on production systems that integrate AI/ML models or LLMs.
Engineering craft - Strong Python, Go, or Java, system architecture, API design, testing, and secure coding practices.
Agentic systems - Experience designing and building agent orchestration, tool-use systems, and autonomous workflows; familiarity with frameworks like LangGraph or similar, or having built equivalent from scratch
Backend engineering - Experience building production APIs and services (FastAPI or similar); async programming, service architecture, high-availability, and reliability patterns (retries, circuit breakers, backpressure)
LLM integration - Hands-on experience integrating LLMs via SDKs and APIs; context engineering, structured outputs, tool calling, and model routing
RAG & retrieval - Experience with embedding pipelines, vector databases (e.g., Milvus, Qdrant, Pinecone), chunking strategies, and relevance tuning
Evaluation & observability - Experience designing LLM and agent evals, monitoring AI system quality, and building observability for non-deterministic systems
Nice to Have:
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, container orchestration, deploying and operating production services
Experience with MCP or similar tool-use protocols for agent-to-service communication
Hands-on ML experience - המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.
Requirements:
Must-Have
5-8 years of software engineering experience, with at least 2-3 years focused on AI/ML engineering
Hands-on experience building production-grade LLM applications - RAG, agents, tool use, or fine-tuning
Proven experience designing and running multi-agent systems in production: orchestration patterns, agent state management, retries, and graceful degradation
Experience monitoring and observing AI agents in production - execution tracing, latency tracking, failure detection, and alerting (e.g., LangSmith, Arize, custom observability stacks)
Proficiency with agentic frameworks: LangChain, LangGraph, and/or AWS Bedrock AgentCore
Strong Python skills and comfort working across the full AI application stack
Experience designing and operating MLOps pipelines (model versioning, deployment, monitoring)
Solid understanding of transformer-based models, embeddings, and vector databases (e.g., Pinecone, Weaviate, pgvector)
Comfortable working in cloud environments (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes)
Strong problem-solving skills and ability to work autonomously in a fast-paced environment
Nice-to-Have
Background in cybersecurity - threat detection, SIEM, SOC automation, or security data analysis - a significant plus for this role
Familiarity with networking concepts (SDN, cloud-native networking, BGP, telemetry)
Experience with model evaluation and benchmarking (LLM-as-judge, RAGAS, or custom eval harnesses)
Exposure to MCP (Model Context Protocol) for tool-augmented agentic workflows
Prior experience in enterprise SaaS, networking, or telecom domains
Publications, open-source contributions, or projects in the LLM/GenAI or agentic AI space
Our Stack
Python PyTorch OpenAI / Anthropic APIs LangChain LangGraph AWS Bedrock AgentCore LangSmith Kubernetes Kafka Elasticsearch AWS PostgreSQL GitHub Jira Confluence.
This position is open to all candidates.
 
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05/04/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a highly motivated AI Full stack Engineer with GenAI background in production to join our team and help us shape the future of the Agentic engineering platform (AEP).
What youll do:
At our company, were a platform by developers, for developers. Your role will encompass end-to-end design, implementation, and daily feature delivery across both backend and frontend systems.
You will:
Implement high scale AI-powered features deeply integrated into our platform
Design and build production-grade backend systems serving a wide and growing user base
Build agent-based workflows using frameworks such as AI SDK
Integrate LLMs into real production systems with attention to reliability, latency, observability, and cost
Work across frontend (React + TypeScript) and backend (NodeJS, Python, Go) to deliver complete AI-driven user experiences
Own features end-to-end: design, implementation, testing, deployment, and monitoring
Help define standards and best practices around AI reliability and evaluation
Contribute to technical planning, mentor teammates, and help recruit top talent
Develop retrieval-augmented generation (RAG) pipelines over structured and unstructured data
Our stack includes React + TypeScript on the frontend, and NodeJS + TypeScript, Python, and Golang on the backend, and Vercels AI-SDK + AWS Bedrock + Azure OpenAI for GenAI. We use Kafka + Kafka Connect, Redis, PostgreSQL, MongoDB and other modern infrastructure components.
Requirements:
5+ years of professional software engineering experience
Experience in NodeJS + TypeScript
Strong experience designing and developing complex systems from design to production
Experience dealing with scale and performance-related challenges
Experience building or integrating AI/LLM-powered applications in production or meaningful production systems
Experience building agent workflows and tool integrations
Ability to think critically about model limitations, hallucinations, latency, and cost tradeoffs
A collaborative team player with a can-do approach
Strong written and verbal communication skills in English and Hebrew
Advantages:
Experience with AWS or other cloud platforms
Experience with vercels AI SDK
Experience with embeddings, vector databases, or semantic search
Expierence with AWS Bedrock / Azure Open-AI
Experience building tool-using agents or workflow engines
Experience with AI evaluation, observability, and monitoring
Experience in DevOps-related tools
Experience with PostgreSQL, Kafka, DocumentDB, OpenSearch, Redis.
This position is open to all candidates.
 
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לפני 8 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for driven and talented people like you to join our R&D team and our mission to change the future of cloud security. Ready to dive in and swim with our pod?
As a Software Engineer on the Security Intelligence & Engagement team, youll be part of a domain responsible for closing the loop between security insight and action across the platform.
Our team builds the systems that transform large-scale cloud security data into meaningful risk insights, such as risk scores, trends, and contextual signals, and the experiences that drive customer response, including alerts, notifications, and guided remediation missions.
Youll work on scalable backend services and distributed systems that power how security insights are generated, aggregated, and delivered to users. The team operates across multiple product domains to ensure that insights lead directly to action, enabling customers to prioritize and resolve risks effectively.
This role is a great opportunity to work on high scale cloud security systems, collaborate across teams, and contribute to building reliable services that sit at the center of platform.
On a typical day youll:
Design and implement backend services that generate and deliver security insights and engagement workflows
Write clean, maintainable, and well-tested code that meets production quality standards
Build scalable systems that process and aggregate large volumes of cloud security signals
Collaborate with product managers, engineers, and designers to translate insights into actionable user experiences
Troubleshoot and resolve complex system issues while improving system reliability and observability
Contribute to architectural discussions and help evolve services to support growing scale and new capabilities
Implement new features following Agile development practices and established engineering standards
Continuously improve system performance, scalability, and maintainability
Requirements:
Bachelors degree in Computer Science, Engineering, or relevant experience
3+ years of professional software development experience
Experience building backend services or data driven systems
Familiarity with microservice architectures and cloud native environments
Strong understanding of software engineering fundamentals including data structures, algorithms, concurrency, and system design
Experience working with databases such as Postgres, Elasticsearch, Redis, or similar
Experience with Python or Go (advantage)
Familiarity with distributed systems or event driven architectures such as Kafka (advantage)
This position is open to all candidates.
 
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31/03/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
The Falcon Cloud Security team is looking for a hands-on Engineering Manager / Team Lead to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will lead a team of talented engineers while remaining deeply technical, helping architect and build autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments.
As a player-coach, you will help shape the "brain" of our cloud security platform, guiding both the people and the technology that leverages large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale.

What You'll Do:

Lead & Grow a Team: Manage, mentor, and develop a team of backend engineers, fostering a high-trust, high-performance culture. Conduct regular 1:1s, support career growth, and drive hiring to scale the team.

Stay Hands-On: Remain an active technical contributor - designing, reviewing, and writing production-quality code alongside your team. Lead by example and maintain a strong engineering presence.

Design & Architect: Drive backend engineering efforts to build autonomous agentic frameworks, guiding the team from rapid prototypes to large-scale production applications.

Develop Core Logic: Contribute to and oversee the development of decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams.

Data Integration: Guide the development of high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning.

Scale Systems: Architect and oversee distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation.

Drive Cross-Functional Collaboration: Partner with Product, Design, and peer engineering teams in a "startup-like" environment to define and deliver new platform capabilities with speed and quality.

Raise the Bar: Champion engineering excellence, new technologies, and best practices across the team and broader engineering organization.
Requirements:
Experience: 8+ years of backend engineering experience, with at least 2 years in an engineering leadership role (Tech Lead, Staff Engineer, or Engineering Manager). Strong proficiency in Go and Python.

People Leadership: Demonstrated ability to hire, mentor, and develop engineers at varying levels. Comfortable balancing technical contribution with team management responsibilities.

AI/LLM Experience: Prior experience building workflows powered by LLMs, RAG, or autonomous agents. Strong understanding of agent frameworks and key components including model integration, tool calling patterns, and Model Context Protocol (MCP).

Cloud Expertise: Deep knowledge of at least two major cloud providers (AWS, Azure, or GCP).

Systems Engineering: Strong understanding of distributed systems, scalability, concurrency, and resilient architecture.

Data Proficiency: Solid experience with data modeling, RDBMS (SQL), and distributed caching solutions like Redis.

Education: BS/MS in Computer Science or equivalent professional experience in data structures and algorithms.
This position is open to all candidates.
 
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31/03/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
The Falcon Cloud Security team is looking for a hands-on Engineering Manager / Team Lead to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will lead a team of talented engineers while remaining deeply technical, helping architect and build autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments.
As a player-coach, you will help shape the "brain" of our cloud security platform, guiding both the people and the technology that leverages large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale.

What You'll Do:

Lead & Grow a Team: Manage, mentor, and develop a team of backend engineers, fostering a high-trust, high-performance culture. Conduct regular 1:1s, support career growth, and drive hiring to scale the team.

Stay Hands-On: Remain an active technical contributor - designing, reviewing, and writing production-quality code alongside your team. Lead by example and maintain a strong engineering presence.

Design & Architect: Drive backend engineering efforts to build autonomous agentic frameworks, guiding the team from rapid prototypes to large-scale production applications.

Develop Core Logic: Contribute to and oversee the development of decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams.

Data Integration: Guide the development of high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning.

Scale Systems: Architect and oversee distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation.

Drive Cross-Functional Collaboration: Partner with Product, Design, and peer engineering teams in a "startup-like" environment to define and deliver new platform capabilities with speed and quality.

Raise the Bar: Champion engineering excellence, new technologies, and best practices across the team and broader engineering organization.
Requirements:
Experience: 8+ years of backend engineering experience, with at least 2 years in an engineering leadership role (Tech Lead, Staff Engineer, or Engineering Manager). Strong proficiency in Go and Python.

People Leadership: Demonstrated ability to hire, mentor, and develop engineers at varying levels. Comfortable balancing technical contribution with team management responsibilities.

AI/LLM Experience: Prior experience building workflows powered by LLMs, RAG, or autonomous agents. Strong understanding of agent frameworks and key components including model integration, tool calling patterns, and Model Context Protocol (MCP).

Cloud Expertise: Deep knowledge of at least two major cloud providers (AWS, Azure, or GCP).

Systems Engineering: Strong understanding of distributed systems, scalability, concurrency, and resilient architecture.

Data Proficiency: Solid experience with data modeling, RDBMS (SQL), and distributed caching solutions like Redis.

Education: BS/MS in Computer Science or equivalent professional experience in data structures and algorithms.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Software Engineer to join our CI Infrastructure team within the Platform Engineering organization.
The team designs, builds, and operates the internal engineering platform that powers our companys build, test, and security validation workflows. This includes large-scale orchestration of complex test environments, hybrid cloud/on-prem execution infrastructure, DevSecOps integrations (SCA, SAST, policy enforcement), and advanced optimization mechanisms.
Our mission is to provide a scalable, reliable, and intelligent CI platform that enables hundreds of engineers to build and validate a complex distributed networking product efficiently and safely.
This is a hands-on engineering role focused on scalability, observability, reliability, and intelligent automation, with direct impact on engineering velocity and release confidence.
What Youll Do
Design and evolve scalable CI infrastructure for build and large-scale test execution
Develop automation and orchestration systems across hybrid environments (AWS and on-prem)
Integrate and optimize security validation flows (SCA, SAST, quality gates) within CI
Improve reliability, performance, and observability across high-volume CI workloads
Develop AI-assisted tooling and agents to optimize test selection, failure analysis, and resource utilization
Analyze CI data to identify bottlenecks, flakiness patterns, and optimization opportunities
Collaborate with R&D, Automation, and Security teams to continuously improve CI architecture and best practices
Take ownership of critical platform components used daily by large engineering teams.
Requirements:
What Were Looking For
B.Sc. in Computer Science or equivalent practical experience
5+ years of hands-on software engineering or infrastructure development experience
Strong programming skills in Python (or similar high-level language)
Experience designing and building scalable systems or automation frameworks
Solid understanding of Linux, containers (Docker), and Git-based workflows
Experience working in cloud and hybrid infrastructure environments
Strong system-level thinking and troubleshooting skills
Ability to take ownership and drive solutions end-to-end
Nice to Have
Experience with CI/CD systems (Jenkins, GitHub Actions, or similar)
Background in large-scale test infrastructure or build systems
Experience integrating security tools (SCA, SAST, SBOM, vulnerability management)
Experience building AI-assisted developer productivity tools
Familiarity with observability stacks (metrics, logs, tracing)
Experience improving reliability and performance of large engineering platforms
Personal Qualities
Strong ownership mindset and sound engineering judgment
Passion for building scalable, reliable infrastructure
Data-driven approach to optimization and continuous improvement
Excellent communication and cross-team collaboration skills
Comfortable operating in complex, distributed environments.
This position is open to all candidates.
 
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לפני 9 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a highly skilled and motivated Senior II Software Engineer to join the Operational Experience engineering team. The team is part of the Customer Experience group, which is responsible for the platform, tools, and customer-facing experiences that power how our customers interact with our ecosystem. This is a high-impact, hands-on role, in which youll be working closely with product managers, designers, customer-facing teams, and engineering partners across the company.
You will operate at the intersection of backend engineering, data-intensive systems, platform development, and customer experience. The ideal candidate brings strong expertise in Node.js and TypeScript, along with deep experience working with large-scale data stores, event-driven pipelines, data models, and high-throughput infrastructure. You will work closely with cross-functional partners to design and implement robust backend services, data-access patterns, and operational workflows that power the portal and internal tools. As we invest heavily in Agentic AI, you will also play a central role in shaping and implementing AI-driven capabilities across the platform. While the role is primarily backend, you will occasionally contribute across the full stack when it supports end-to-end delivery.
If you enjoy owning complex problems end to end, improving systems at scale, and building experiences that bring real value to customers, we would love to meet you.
What you'll be doing:
Drive technical direction and architecture within the OX team and across the broader CX organization. You will proactively identify opportunities to improve performance, resilience, cost, scalability, and developer experience, primarily in backend systems but with influence across the stack.
Lead the development of AI-driven and Agentic AI capabilities. Define how LLMs integrate into our platform, build AI-powered workflows, and establish strong engineering patterns for safe and reliable adoption.
Own and evolve the data foundations behind the portal. Optimize pipelines, improve data quality and freshness, and design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, MySQL, and related systems.
Work closely with product, design, customer-facing teams, and partner engineering groups. Turn ambiguous problems into clear execution plans and ensure alignment with customer and business goals.
Shape shared standards and platform best practices. Guide other teams on backend services, data integration patterns, portal development approaches, and AI-enabled workflows.
Mentor and elevate engineers across the CX group. Promote engineering excellence, share knowledge openly, and help teams adopt effective modern development practices.
Own delivery of high-impact initiatives. Contribute hands-on when needed, remove blockers, maintain execution momentum, and drive projects from concept to production.
דרישות:
6+ years of experience as a software engineer with strong expertise in backend development using Node.js and TypeScript, with the ability to work across the stack when needed.
Experience building customer-facing products and working closely with product managers, designers, and customer-facing stakeholders.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Hands-on experience with distributed systems, event-driven architectures, and datastores such as Redis, Kafka, SQS, Elasticsearch, MySQL, and Snowflake.
Demonstrated impact in senior engineering roles. You have led complex technical initiatives, influenced product decisions, and helped drive architecture across teams.
Deep systems thinking with the ability to design and scale robust, performant, and maintainable services.
Excellent communication and collaboration skills. You can discuss architecture with engineers, roadmap with product managers, and explain tradeoffs to non-technical stakeholders.
Experience using modern AI development tools.# המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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דיווח על תוכן לא הולם או מפלה
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
29/03/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking We are seeking an experienced Senior Generative AI Engineer (LLMs & Agents) to join our AI squad at KPMG. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work.
You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms.
You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities:
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Pytho
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliability, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS
Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.)
Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques
Define and refine best practices for GenAI system development and deployment
Contribute to internal accelerators, methodologies, and knowledge sharing
Requirements:
Technical Expertise:
Advanced proficiency in Python for backend development and AI systems
Deep understanding of large language models and generative AI techniques
Hands-on experience designing and implementing multi-agent architectures
Advanced prompt engineering and orchestration strategies
Strong background in microservices architecture, API development, and production system design
Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience
3-4+ years of experience in AI/ML development with significant GenAI project exposure
Proven experience in end-to-end software development in Python
Proven experience deploying and maintaining AI systems in production
Client-facing experience in technical consulting or solution delivery roles
Advantages:
Hands-on experience developing directly against LLM provider SDKs and APIs (e.g., OpenAI, Anthropic, Google), including tool/function calling, streaming, and advanced orchestration patterns
Docker and Kubernetes experience
OCR systems and document intelligence experience
Data pipeline development and maintenance experience
Education & Background:
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related field (or equivalent demonstrated industry experience)
Soft Skills:
Strong problem-solving and analytical capabilities
Excellent technical communication skills
Ability to collaborate effectively across teams
Adaptability in fast-paced, evolving technical environments
Consulting mindset with strong client focus
This position is open to all candidates.
 
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