דרושים » מחשבים ורשתות » Sr. MLOps Engineer - Falcon Cloud Security

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לפני 10 שעות
דרושים בCrowdStrike
Location: Tel Aviv-Yafo
Job Type: Full Time
CrowdStrike's Data Science Studio is seeking a pioneering Senior MLOps Engineer to establish and lead our MLOps function from the ground up. As the first MLOps engineer in the studio, you will play a foundational role in shaping how we build, deploy, and scale machine learning systems that protect thousands of organizations worldwide.

This is a unique opportunity to define the technical strategy, influence the technology stack, and architect the infrastructure that will power our AI/ML-driven security solutions for years to come.

This role combines strategic vision with hands-on execution. You'll work at the intersection of data science, engineering, and production operations - building production-grade systems that operate at immense scale while collaborating closely with highly technical data scientists and ML engineering teams across CrowdStrike.

What You'll Do:
- Architect MLOps infrastructure from the ground up: Design and implement the foundational MLOps platform, establishing best practices, tooling, and workflows that will scale with our growing data science initiatives
- Define technology strategy: Evaluate, select, and integrate MLOps technologies and platforms that best serve our needs - from experiment tracking and model versioning to deployment pipelines and monitoring systems
- Build production-grade ML pipelines: Develop robust, scalable pipelines for model training, validation, deployment, and monitoring that handle massive data volumes and ensure reliability in production
- Enable data scientist productivity: Create tools, frameworks, and automation that empower data scientists to move quickly from research to production while maintaining high quality and reliability standards
- Establish monitoring and observability: Implement comprehensive monitoring, logging, and alerting systems to ensure ML models perform optimally in production and issues are detected proactively
- Drive MLOps culture and practices: Champion best practices in ML engineering, CI/CD for ML, model governance, and reproducibility across the data science organization
- Collaborate cross-functionally: Partner closely with data scientists to understand their workflows and pain points, and work with ML engineering teams to ensure seamless integration with broader platform capabilities
 -Scale for the future: Design systems with scalability, security, and maintainability in mind, anticipating the needs of a rapidly growing ML portfolio
Requirements:
- 6+ years of experience in MLOps, ML engineering, DevOps, or related infrastructure roles with focus on machine learning systems
- Production ML systems expertise: Proven track record of building and operating ML systems at scale in production environments
- Strong infrastructure and automation skills: Deep knowledge of cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, CloudFormation)
- ML pipeline proficiency: Hands-on experience with ML workflow orchestration tools (e.g., Airflow, Kubeflow, MLflow, Metaflow) and building end-to-end ML pipelines
- Programming excellence: Strong coding skills in Python; experience with additional languages is a plus
- CI/CD and DevOps practices: Expertise in building automated deployment pipelines, version control, and modern DevOps methodologies
- Strategic and hands-on balance: Ability to think architecturally about long-term solutions while rolling up your sleeves to implement them
- Collaborative mindset: Excellent communication skills and ability to work effectively with data scientists, engineers, and stakeholders with varying technical backgrounds
- Startup mentality: Comfort with ambiguity and ability to build from scratch in a fast-paced environment
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Engineering Team Lead
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions - customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
As the AI Team Lead, you will guide a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll combine technical depth with leadership skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Leadership & Team Management:
Lead, mentor, and grow a team of machine learning engineers and data scientists.
Foster a culture of technical excellence, collaboration, and continuous learning.
Define team goals, measure progress, and ensure high-quality deliverables.
Strategy & Roadmap:
Own the data science strategy and align it with company objectives.
Identify opportunities for applying machine learning and generative AI across products and internal systems.
Evaluate emerging technologies, tools, and methodologies to keep the team ahead of the curve.
Hands-On Technical Work;
Design, prototype, and implement ML models, including LLM-powered copilots, retrieval systems, and fraud detection pipelines.
Guide the deployment of models into production environments with scalability and reliability in mind.
Ensure best practices for experimentation, evaluation, and monitoring.
Cross-Functional Collaboration:
Work closely with engineering to integrate ML components into production systems.
Partner with product managers to align solutions with customer needs and business priorities.
Collaborate with security and compliance teams to ensure ethical and secure use of data.
Requirements:
Proven experience leading backend or ML-platform engineering teams (2+ years in a leadership role), including mentoring engineers and driving architectural decisions.
Excellent coding skills in Python/TypeScript, with hands-on experience building reliable backend services and tooling. Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) is a strong advantage.
Experience designing, deploying, and maintaining production systems that integrate ML components, including APIs, microservices, model serving layers, feature pipelines, monitoring, and CI/CD/MLOps workflows.
Solid understanding of distributed systems concepts, performance optimization, observability, and operating services at scale.
Strong communication skills, with the ability to bridge technical, product, and business perspectives.
Prior experience in cybersecurity, fraud prevention, or identity management is a plus, especially with secure system architectures or ML-augmented decisioning systems.
This position is open to all candidates.
 
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22/03/2026
Job Type: Full Time
We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.

Optimizing AI models and agents for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Monitoring and deploying agentic systems, LLMs, and ML models in production.

Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.

Collaborating closely with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Collaborating with DevOps teams to integrate pipelines and workflows into the CI/CD process, ensuring flawless deployments and rollbacks.

Building and maintaining monitoring and alerting systems to proactively identify and resolve issues relating to quality, performance and infrastructure.

Implementing access controls, authentication mechanisms, and encryption standards for AI models and data.

Documenting guidelines, and standard operating procedures for MLOps/AI processes and sharing knowledge with the wider team.

Develop proof-of-concepts for new features.
Requirements:
What we need to see:

BSc/MSc in CS/CE or related field (or equivalent experience).

Strong background in AI with experience deploying and monitoring AI/ML models, LLMs and agents to production systems at scale, including distributed and multi-node environments - at least 5 years of experience.

Proficiency in programming languages such as Python, Java, or Scala, along with experience in using ML/AI frameworks and libraries (e.g. TensorFlow, PyTorch).

Proficiency in microservices architecture, container orchestration, cloud platforms, and scalable infrastructure for training and inference workloads.

Knowledge of inference optimization techniques.

Understanding of build infrastructure and CI/CD tools and practices (e.g. GitLab, GitHub Actions, Jenkins).

You are detail-oriented and care deeply about robust, well tested, high-performance code in production environments.

You are proactive, take full ownership of your deliverables, have a can-do approach, and excellent communication and collaboration skills, able to work effectively in multifunctional teams.

Ways to stand out from the crowd:

Knowledge of network protocols and Linux internals.

Security and networking background, with knowledge of security protocols, network architectures, firewalls, intrusion detection systems, and other relevant security and networking concepts.

Experience deploying and optimizing generative models and agents.

Knowledge of network security principles and practices.
This position is open to all candidates.
 
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7 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
Required ML Engineering Team Lead - Applied AI Engineering Group
The Dream Job
It starts with you - a technical leader driven to build both the ML platform and the engineering team behind it. You care about reliable infrastructure, great developer experience, and growing engineers through real ownership. You'll set the technical direction for our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - shaping how models reach production across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments. You stay close enough to the codebase to debug production issues, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the ML platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Set technical direction for the ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - through RFCs, prototypes, design reviews, and build-vs-buy decisions
Lead and grow a team of ML Engineers - hire, mentor, pair on hard problems, and raise the bar through code and design reviews
Contribute to critical systems, debug production issues, and maintain deep context on the codebase to inform technical decisions
Own operational excellence for model serving - set and enforce SLAs, run capacity planning, and keep compute costs predictable
Establish ML engineering standards - reproducible experiments, automated evals, model packaging, CI/CD for models, and observability
Support the full lifecycle of our models - from training on domain-specific data to low-latency inference powering production systems
Work closely with Data Platform, AI, Data Science, and Product teams - translate business priorities into engineering work and manage cross-team dependencies
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as model performance.
Requirements:
6+ years in software engineering, ML engineering, or platform engineering, with hands-on experience building and operating ML infrastructure at scale.
2+ years leading an engineering team - hiring, mentoring, conducting design reviews, and shipping alongside your team
Engineering craft - Strong Python, distributed systems design, testing, secure coding, API design, CI/CD discipline, and production ownership.
ML platform & serving - Model serving frameworks (e.g., Triton, TorchServe, vLLM, Ray Serve); model packaging, deployment pipelines, and inference optimization
Training infrastructure - Distributed training pipelines (e.g., frameworks like PyTorch, JAX) experiment orchestration and reproducibility
ML lifecycle tooling - Feature stores, model registries, experiment tracking (e.g., MLflow, Weights & Biases); dataset versioning and lineage
Data pipelines - Building training and inference data pipelines; familiarity with tools like Spark, Airflow/Dagster, and streaming ingestion
Comfortable with AI coding tools like Cursor, Claude Code, or Copilot
Nice to Have:
Experience operating in constrained environments - on-premise, private cloud, or air-gapped deployments
Hands-on experience with simulation environments, synthetic data generation, or reinforcement learning workflows
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, observability, incident response
Hands-on data science or applied ML experience.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.
Requirements:
To thrive in this role, youll need:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills - in Java & Python
Experience with TensorFlow - a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.
This position is open to all candidates.
 
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a motivated and experienced Machine Learning Platform Engineer to join our dynamic team.

In this role, you will collaborate closely with data scientists and DevOps professionals to design and build the infrastructure, ecosystem libraries, and pipelines that power our data science initiatives. You will take ownership of model development, monitoring, and maintenance, working hand-in-hand with data scientists on a daily basis.

If youre passionate about AI, machine learning, and writing high-quality code-and are eager to contribute to innovative, impactful do good projects in the digital health space-wed love to hear from you!

What you'll be doing:
Design, develop, and maintain our machine learning ecosystem libraries.
Build and manage data science code, Docker images, and Kubeflow Pipelines (KFP).
Create and maintain CI scripts to ensure seamless integration and delivery.
Conduct thorough code reviews to uphold high-quality standards.
Collaborate closely with data scientists, understanding and addressing their evolving needs.
Work alongside software developers to seamlessly integrate machine learning models into production systems.
Stay current with the latest advancements in machine learning, leveraging innovative techniques to enhance the companys products and services.
Requirements:
What we're looking for:
5+ years in software engineering with experience in backend/platform roles.
5+ years of experience with Python.
Proficiency in another language, such as C++, Rust, Java, or Go, is an advantage.
2+ years of experience working with cloud platforms such as Google Cloud (preferred), Azure, or AWS, including familiarity with ML workflow frameworks like KFP or Vertex Pipelines.
Solid experience in ML/AI development (a must).
Experience with inference optimization (vLLM) and fine-tuning (Axolotl/Huggingface).
Expertise with transformers, PyTorch, CUDA, and other low-level ML libraries.
Familiarity with Docker and Kubernetes.
Excellent problem-solving skills and a proactive attitude, with a strong focus on code quality and optimization.
Collaborative mindset with the ability to work closely with cross-functional teams. Strong communication and teamwork skills are essential.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives us toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.
דרישות:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQ המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Realize your potential by joining the leading performance-driven advertising company!
As a Senior MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.
Requirements:
To thrive in this role, youll need:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills - in Java & Python
Experience with TensorFlow - a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an ML Engineer / MLOps Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.
You will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle management-the foundation of our product.
Responsibilities:
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.
End-to-end ML delivery - enabling model performance development, training, validation, testing, and version control.
Build and support monitoring and observability tools - dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as: Feature Store, Vector / Graph Databases.
Data wrangling - supporting and enabling data requirements for research, training, validation, and testing.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Requirements:
3+ years of experience as an ML Engineer / MLOps
5+ years of experience as a software engineer or data engineer
2+ years of experience in a technical leadership role (leading engineers or data scientists)
Strong programming skills in Python and SQL
Hands-on experience with MPP frameworks such as Spark, Flink, Ray, Dask or equivalent
Strong analytical and critical thinking skills
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8600846
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7 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. 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. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.
Requirements:
6+ years in backend software engineering, with 4+ years focused on production systems that integrate AI/ML models or LLMs.
2+ years leading an engineering team - hiring, mentoring, conducting design reviews, and shipping alongside your team.
Engineering craft - Strong Python, Go, or Java, system architecture, API design, testing, and secure coding practices.
Agentic systems & LLM integration - Deep understanding of agent orchestration, tool-use architectures, LLM integration patterns, context engineering, and frameworks like LangGraph or similar, or custom-built equivalents
Backend & platform engineering - Experience building and operating production APIs, services, and platform infrastructure at scale; comfortable working with relational databases, message queues, and event-driven architectures
RAG & retrieval - Experience with production RAG pipelines, vector databases, embedding systems, and retrieval quality
Evaluation & observability - Experience building LLM and agent eval infrastructure, monitoring AI quality, and observability for non-deterministic systems
Nice to Have:
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, service architecture, incident management
Experience with MCP or similar tool-use protocols for agent-to-service communication
Hands-on ML experience - model training, fine-tuning, or working directly with ML pipelines.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8603446
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דיווח על תוכן לא הולם או מפלה
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סגור
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As a DevOps Experience Manager at Fiverr, you will lead our DevEx team with a specific focus on optimizing the end-to-end journey of our software engineers. Your mission is to build and maintain a scalable, secure, and intuitive internal developer platform that minimizes friction and maximizes productivity. You will drive the adoption of modern DevEx practices, ensuring a seamless alignment between engineering workflows, developer satisfaction, and operational excellence. This leadership role requires a balance of hands-on technical expertise and strategic vision, empowering your team to deliver high-quality platform solutions in a fast-paced environment. You will shape Fiverr’s developer productivity strategy - optimizing the "inner loop," enhancing system reliability, and implementing innovative technologies, including Generative AI-driven automation , to provide developers with better self-service capabilities and insights.

What am I going to do?:
Lead and mentor a team of engineers dedicated to developer productivity, fostering a culture of ownership and continuous improvement. Design and implement scalable, secure, and cost-efficient developer platforms and architectures that simplify the path to production. Evaluate and adopt emerging tools and best practices to enhance the developer experience and overall product quality. Drive standards of Infrastructure as Code, comprehensive observability, and automated testing to create a "paved road" for development teams. Monitor productivity metrics and infrastructure reliability, providing data-driven insights to leadership on how to improve engineering velocity. Guide the team in applying GenAI-native tools to automate documentation, provide self-service support for developers, and optimize performance. Partner with cross-functional leaders to influence architecture and development workflows, ensuring the platform meets the needs of all engineering teams. Hire and continue to build the team Report to the VP of Cloud Engineering , contributing to Fiverr's long-term technology roadmap for developer empowerment.

Equal opportunities:
At Fiverr, we’re not about checklists. If you don’t meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you. At Fiverr, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. Fiverr is proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, Fiverr will provide accommodation to individuals with disabilities or a special need.
Requirements:
8+ years of hands-on experience in DevOps or Platform Engineering, with at least 1+ years in a leadership/management role Proven experience leading teams and driving alignment within matrixed organizations. Technical expertise in CI/CD pipelines, AWS, Infrastructure as Code (Terraform, Pulumi), container orchestration (Kubernetes), and observability tools. Strong understanding of how infrastructure choices impact developer velocity and cloud cost modeling. Experience with Generative AI in a DevEx context, such as automating workflows, enhancing productivity, or creating intelligent alerting systems. Curiosity and ability to evaluate new AI-native tools and integrate them where they provide real value to the engineering community. Excellent communication skills , with the ability to influence both technical developers and non-technical stakeholders. Strategic mindset , comfortable managing competing priorities in a high-pressure environment.
This position is open to all candidates.
 
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עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
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