דרושים » AI » AI DevOPS Engineer 2633

At our company, "It's all about the user. All of them." We're passionate about providing a seamless one-stop experience for business travelers, no matter how they travel, where they stay, or where they're going. we are building cutting-edge solutions at the intersection of travel, expense, payments, and AI. As a leader in the AI for Travel domain, we are using intelligent, practical AI experiences to make business travel simpler, faster, and more reliable for travelers, travel managers, finance teams, and support teams.
We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep our company reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.
This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.
This position is based out of our new Tel Aviv office.
What You'll Do:
Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

MA?LYS is a fast-growing global body care brand, built on a proprietary e-commerce platform, deep consumer insights, and a relentless focus on performance. Millions of women worldwide use our products, and we are on a mission to become one of the most influential body care brands globally.
We operate at extreme velocity, with high standards and an obsession with results. We believe in challenging conventional thinking, making data-driven decisions, and moving quickly from idea to execution.
We are looking for a Head of AI to build and lead MA?LYS' AI transformation journey, serving as a rare opportunity for a highly strategic and deeply hands-on builder who thrives at the intersection of business, technology, and execution. In this role, you will have the ultimate playground to shape how our entire company operates, influence every major function, and create a lasting competitive advantage for a leading body care brand. Initially operating as an individual contributor partnering closely with the CEO and the Management Team. Over time, you will transition to build and lead a small, high-performing team as AI becomes an increasingly critical capability across our global e-commerce and retail operations.
To thrive in our high-pace environment, you must think like an owner, not a consultant, and be equally comfortable discussing macro business strategy with executives as well as writing code to solve a messy problem yourself. You are someone who embraces ambiguity, enjoys building from scratch, and is completely obsessed with execution. You possess the high emotional intelligence and empathy required to collaborate with non-technical stakeholders and build trust, yet you maintain the thick skin, resilience, and great sense of humor needed to handle direct communication and rapid structural pivots. Most importantly, you maintain an uncompromising commitment to quality and process improvement, ensuring that every automation or workflow you deploy actively drives our core business metrics forward without requiring hand-holding or constant reminders.
Your life at MA?LYS will look like…
* Define and lead the company's AI strategy and execution roadmap.
* Identify the highest-impact opportunities for AI across all business functions.
* Prioritize initiatives based on measurable business value, speed of implementation, and scalability.
* Design, build, deploy, and continuously improve AI-powered workflows, tools, automations, and agents.
* Translate business challenges into practical AI solutions that improve performance, efficiency, and decision-making.
* Develop production-ready applications and workflows using modern AI technologies, APIs, agents, and automation frameworks.
* Drive adoption and behavioral change across teams.
* Partner directly with business leaders to identify opportunities and implement solutions.
* Evaluate emerging technologies, models, vendors, and platforms.
* Establish governance, standards, architecture, and best practices for AI development.
* Define and track success metrics for every AI initiative, ensuring measurable impact on growth, productivity, speed, efficiency, or cost.
You will thrive in this role if you have…
* Strong technical foundation in Computer Science, Software Engineering, Data Science, or a related field.
* 5+ years of experience building technology, data, AI, automation, or software solutions in high-performance environments.
* Proven experience identifying business opportunities and translating them into deployed AI products, agents, automations, or workflows that drive measurable business impact.
* Hands-on experience working with modern generative AI technologies, LLMs, agent frameworks, APIs, embeddings, automation platforms, and production deployments.
* Strong proficiency in Python, SQL, APIs, and data-driven application development.
* Deep understanding of business operations, growth metrics, p

we are looking for a Staff AI Engineer, Innovation.
As a Staff AI Engineer in global CTO group, you will play a central role in building the next generation of AI-powered security capabilities across product portfolio. This role is focused on rapid prototyping, experimentation, and innovation, turning emerging ideas into working product features that can scale across multiple products and technology stacks.
You will design and build AI-driven systems end-to-end, from agent-based workflows and model integrations to backend services, data pipelines, and product-facing capabilities. You will work closely with product, engineering, and research teams across the company to explore new use cases, validate ideas quickly, and bring impactful AI features into production.
This role is ideal for an experienced AI engineer who enjoys moving fast, working across boundaries, and building real production systems, not just experiments. Your work will directly influence how AI is embedded across platforms and how customers experience secure AI at enterprise scale.

We are seeking an experienced DevOps Engineer to join our Engineering team and play a key role in building and operating our cloud-native platform. The ideal candidate will have hands-on experience managing production environments at scale, driving cloud transformation initiatives, and supporting the of enterprise systems from on-premises deployments to modern SaaS and cloud-native architectures. You will be responsible for designing, automating, and maintaining scalable infrastructure, CI/CD pipelines, and deployment processes that support both our core products and emerging AI-driven capabilities. Working closely with Engineering, QA, Product, and AI teams, you will help ensure the reliability, security, and performance of our services while driving operational excellence and continuous improvement across our technology stack.
Responsibilities:
Design, implement, and maintain CI/CD pipelines.
Manage and optimize cloud infrastructure across AWS, Azure, and/or GCP.
Develop and maintain Infrastructure as Code using Terraform.
Manage Kubernetes-based environments and GitOps deployment workflows using Argo CD and Kustomize.
Lead and support the migration of enterprise applications and infrastructure from on-premises
environments to scalable SaaS and cloud-native architectures.
Establish, maintain, and continuously improve production environments, ensuring high availability, security, scalability, and operational excellence.
Demonstrate strong production ownership, including incident management, root cause analysis, capacity planning, and performance optimization.
Collaborate with Engineering, QA, Product, and AI teams.
Support the deployment, operation, and monitoring of AI and Generative AI services.
Build and maintain monitoring, logging, and alerting systems.
Troubleshoot and resolve infrastructure, deployment, and production issues.

DRS RADA is a leading defense high-tech company specializing in radar systems development. We are seeking a talented AI Engineer to join our AI group and take part in the research and development of new AI-based capabilities and products. In this role, you will work on a wide range of AI challenges, from early-stage exploration and development to supporting the integration of solutions into operational systems. This role includes working with different radar data modalities and offers an opportunity to contribute to meaningful, cutting-edge technologies in a multidisciplinary environment. Key Responsibilities: · Research, develop, and evaluate AI models and algorithms for new product capabilities. · Explore new ideas and transform them into practical AI-based solutions. · Analyze complex time-series data and extract insights to support model development and product decisions. · Work closely with AI and software engineers within the team and take responsibility to bring new solutions into operational systems. · Develop clean, efficient, and maintainable Python code for model development and experimentation. · Stay updated with industry trends, research methods, and emerging technologies in AI and data science.

We are looking for an experienced SRE Team Lead to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will lead a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 3-4 years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.


What will you do?

Leadership & Team Management

Lead, mentor, and grow a team of SREs, providing technical direction, career development guidance, and day-to-day management.

Own the team roadmap for reliability, observability, and automation initiatives - prioritizing work, removing blockers, and driving delivery.

Conduct regular 1:1s, performance reviews, and hiring processes to build and sustain a high-performing team.

Foster a culture of operational excellence, blameless post-mortems, and continuous improvement.

Act as an escalation point for complex incidents and reliability issues, leading post-incident reviews and ensuring follow-through on action items.


Automation & Infrastructure

Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.

Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.

Drive the adoption of infrastructure-as-code practices across the organization.

Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.


Monitoring & Observability

Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.

Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.

Define and track SLIs, SLOs, and error budgets across key services.

Partner with development teams to embed observability earlier in the software development lifecycle.


Database & Platform Support

Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.

Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.

We are seeking an experienced Generative AI Engineer to join our AI squad. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities:
GenAI Development & Implementation:
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation:
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment

We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.

You will join our Media & Telecom division, building and operating mission-critical TV and streaming platforms used by global telecom operators.

This is a hands-on DevOps + SRE hybrid role, focused on engineering, reliability, and large-scale production systems. The team is responsible for designing, improving, and operating highly available services in a fast-moving, production-driven environment.

You will work closely with R&D, NOC, and Product teams, taking ownership of system behavior in production and driving continuous improvements in scalability, performance, and automation.

The day-to-day
Design, build, and improve scalable, highly available systems running on AWS
Work deeply with Kubernetes (K8s), Docker, and Helm charts in production environments
Build and maintain CI/CD pipelines (Jenkins, Argo Workflows) to support rapid and reliable delivery
Develop and manage infrastructure using Terraform (Infrastructure as Code)
Troubleshoot and resolve complex issues in distributed systems across application, infrastructure, network, data, and observability layers
Improve system reliability, monitoring, and observability using tools such as Prometheus, Coralogix (or similar)
Build, integrate, and operate AI-based systems and agents as part of production services
Collaborate with R&D, NOC, and Product teams to drive system improvements and resolve production challenges
Take part in on-call rotations as part of shared production ownership

We are looking for a passionate and skilled Senior DevOps Engineer to join our team. The ideal candidate is a proactive problem-solver with extensive experience in architecting and maintaining high-scale, production grade SaaS environments across multiple cloud providers.
As a Senior DevOps Engineer, you will be part of a high-performing team, leading the company infrastructure. You will work in a dynamic and agile environment with the most cutting edge technologies.
Responsibilities:
Design and plan large-scale, multi-cloud (GCP, AWS, Azure) production architectures, ensuring compliance with strict SLAs.
Automate infrastructure provisioning using tools like Terraform/Terragrunt, and leveraging GitOps methodologies.
Implement and maintain CI/CD pipelines to support multiple development teams.
Establish best practices for observability, logging, and alerting using technologies such as Datadog, Coralogix, OpenTelemetry, and Prometheus/Grafana.
Drive continuous improvement in system reliability, scalability, and cost efficiency across all environments.
Manage and operate message brokers (RabbitMQ), databases (MySQL, Redis), at scale.
Mentor engineers, fostering a strong DevOps culture and establishing standard practices within the organization.