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לפני 20 שעות
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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 Navan 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.
Requirements:
5+ years of experience as a Senior SRE, Infrastructure Software Engineer, Production Engineer, or DevOps Engineer.
3+ years of experience operating production, 24x7 customer-facing systems.
Hands-on experience delivering production infrastructure, platform tooling, and automation used by engineering teams.
Strong software engineering skills in Python, Go, Java, or a similar language, with a bias toward production-quality code, tests, monitoring, and documentation.
Experience with cloud infrastructure, container orchestration, Linux systems, networking, CI/CD, and infrastructure as code such as Terraform or CloudFormation.
Experience building, tuning, and automating observability systems such as Grafana, Prometheus, New Relic, Datadog, Splunk, or similar tools.
Familiarity with SLOs, incident response, on-call practices, root cause analysis, and blameless postmortems.
Practical experience or strong interest in AI solutions, AI providers, agents, AI APIs, provider integrations, or AI-assisted internal tools.
Ability to troubleshoot AI tools and provider/API issues, including rate limits, quota, auth, permission errors, latency, SDK or API contract changes, content quality issues, and service degradations.
Excellent communication skills and the ability to work with stakeholders and domain experts across the company.
This position is open to all candidates.
 
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לפני 20 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Software Engineer to own and evolve the runtime platform that powers production AI agents.

This is a hands-on backend and platform engineering role for someone who combines deep TypeScript expertise, strong distributed-systems fundamentals, and exceptional production debugging skills with a practical understanding of LLMs and agentic systems.

You will work closely with engineers building AI agents. Your responsibility will be to provide the reliable runtime, infrastructure, abstractions, and observability they need to deliver new capabilities safely and quickly.

What youll do

Own and evolve the production runtime responsible for executing and orchestrating AI agents.
Design platform capabilities for agent execution, tool calling, streaming, state management, persistence, and long-running workflows.
Build resilient integrations with multiple LLM providers and model-serving platforms.
Design provider-routing and fallback strategies based on availability, latency, quality, and cost.
Implement retries, timeouts, circuit breakers, rate-limit handling, idempotency, and graceful degradation.
Ensure the platform remains available when external dependencies or infrastructure components experience outages.
Build reliable mechanisms for loading, caching, versioning, and recovering agent configurations and artifacts.
Create end-to-end observability for AI requests, including model, provider, agent, latency, token usage, cost, errors, retries, and fallback behavior.
Define dashboards, alerts, SLOs, and runbooks for production AI workloads.
Lead the investigation of complex production issues across application code, infrastructure, external providers, distributed state, and agent behavior.
Improve platform scalability, concurrency, latency, and resource efficiency.
Build reusable APIs and abstractions that allow agent developers to add capabilities without duplicating infrastructure logic.
Strengthen platform quality through integration testing, load testing, failure injection, and dependency-outage simulations.
Turn production incidents into architectural improvements, automated tests, monitoring, and operational safeguards.
Collaborate with product, infrastructure, and engineering teams to translate customer and business requirements into platform capabilities.
Mentor engineers and establish best practices for building and operating reliable production AI systems.
Requirements:
7+ years of professional software engineering experience, primarily in backend, platform, or distributed systems.
Expert-level TypeScript and Node.js skills.
Experience with NestJS or a comparable backend framework.
Proven experience designing, building, and operating large production services.
Strong understanding of distributed-systems patterns, including retries, backoff, idempotency, circuit breakers, caching, consistency, and failure recovery.
A systematic debugging mindset and the ability to trace failures across multiple services and dependencies.
Experience owning customer-facing systems where availability, latency, and correctness directly affect users.
Strong experience with cloud infrastructure and managed services, preferably AWS.
Experience with distributed caching and storage technologies such as Redis and S3.
Hands-on experience with production observability: structured logs, metrics, tracing, dashboards, alerts, and SLOs.
Experience participating in incident response and driving follow-up improvements.
Strong API design, testing, and software architecture fundamentals.
Excellent communication and collaboration skills across engineering, product, infrastructure, and AI teams.
Bachelors degree in Computer Science or a related field, or equivalent practical experience.
This position is open to all candidates.
 
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05/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.
Requirements:
Your Experience:
4+ years operating production infrastructure in AWS.
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Strong experience with observability and alerting in Datadog or comparable platforms.
Solid grounding in Linux, networking, cloud security, and reliability best practices.
Strong scripting skills in Python and Bash.
Proven ability to own platform projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset - comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work.
Key qualities
Ownership-driven - You take responsibility for the systems you build and operate, from design through production support and continuous improvement.
Collaboration - You work effectively across engineering, security, product, and leadership to align priorities and drive shared outcomes.
Developer experience focus - You are committed to reducing friction for engineering teams through thoughtful automation, self-service workflows, and reliable internal tooling.
Innovation balanced with pragmatism - You actively explore new approaches, particularly in AI-assisted operations, while weighing them against reliability, maintainability, and operational simplicity.
Security mindset - You design and build with least privilege, auditability, and production safety as foundational principles rather than afterthoughts.
Clear communication - You articulate infrastructure, reliability, cost, and security tradeoffs precisely to both technical and non-technical stakeholders.
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 a fast-paced, technology-driven team where everyone's contribution impacts product success.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.

This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.

The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.

Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.

What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.

Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.

This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help our company move faster, automate smarter, and turn ideas into measurable business wins.

What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.
דרישות:
2-5 years of hands-on experience in AI Engineering, Data Engineering, Software Engineering, Data Science, Analytics Engineering, or a similar technical role.
Proven experience building and deploying AI-powered products, workflows, agents, automations, or business solutions in a real company environment.
Strong hands-on experience with LLMs, AI agents, prompt engineering, RAG, workflow automation, APIs, or AI development frameworks.
Ability to code and build practical solutions using Python, SQL, JavaScript/TypeScript, or similar languages.
Strong data experience, including ETLs, data pipelines, APIs, databases, data warehouses, and Snowflake.
Experience working in a SaaS or B2B technology company.
Strong business acumen, ownership, and communication skills, with the ability to work independently with stakeholders and drive projects from idea to production.
Degree in Engineering, Computer Science, Mathematics, Statistics, Physics, or a related quantitative field - advantage
Advantages
Experience with agent frameworks, RAG systems, vector databases, orchestration tools, Snowflake, Airflow, Rivery, Gitlab, Claude, OpenAI, or similar tools.
Experience working in a cybersecurity or data company.#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.
Requirements:
Your Experience:
4+ years operating production infrastructure in AWS.
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Strong experience with observability and alerting in Datadog or comparable platforms.
Solid grounding in Linux, networking, cloud security, and reliability best practices.
Strong scripting skills in Python and Bash.
Proven ability to own platform projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset - comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work.
Key qualities
Ownership-driven - You take responsibility for the systems you build and operate, from design through production support and continuous improvement.
Collaboration - You work effectively across engineering, security, product, and leadership to align priorities and drive shared outcomes.
Developer experience focus - You are committed to reducing friction for engineering teams through thoughtful automation, self-service workflows, and reliable internal tooling.
Innovation balanced with pragmatism - You actively explore new approaches, particularly in AI-assisted operations, while weighing them against reliability, maintainability, and operational simplicity.
Security mindset - You design and build with least privilege, auditability, and production safety as foundational principles rather than afterthoughts.
Clear communication - You articulate infrastructure, reliability, cost, and security tradeoffs precisely to both technical and non-technical stakeholders.
This position is open to all candidates.
 
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29/07/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
Experience & Leadership:

3-4+ years of experience in a people management or team lead capacity within SRE, DevOps, or infrastructure engineering.

5-8+ years of overall experience in SRE, DevOps, or infrastructure automation roles.

Proven track record of building, coaching, and retaining high-performing engineering teams.

Experience owning an engineering roadmap and driving cross-functional reliability initiatives.


Technical Skills :

Strong scripting skills in Python and Bash; comfortable building and maintaining production-grade automation.

Hands-on experience with infrastructure automation tools, particularly Ansible.

Solid experience with monitoring and observability platforms - ELK stack, Grafana, and Zabbix.

Good understanding of CI/CD pipelines and related tooling, including Jenkins.

Familiarity with managing and monitoring MongoDB and PostgreSQL in a production environment.

Comfortable working in Linux-based environments.

Excellent problem-solving skills and strong written and verbal communication.


Ability to support the following:

Experience with cloud providers - AWS, GCP, or Azure.

Exposure to containerization technologies such as Docker and Kubernetes.

Familiarity with infrastructure provisioning using Terraform.

Experience introducing SRE practices (SLOs, error budgets, chaos engineering) at an organizational level.

Exposure and experience with migrating/ building AI tools to improve process.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
5+ years of experience as a DevOps Engineer or similar
infrastructure-focused role.
Hands-on experience with Azure, Aws, or GCP.
Experience with CI/CD tools such as Jenkins, GitHub Actions, or similar platforms.
Strong knowledge of Terraform and Infrastructure as Code practices.
Experience with Docker, Kubernetes, Argo CD, and Kustomize.
Experience designing and operating production-grade Kubernetes saas platforms or enterprise environments.
Experience with monitoring and observability tools such as Prometheus, Grafana, and ELK.
Strong troubleshooting, analytical, and communication skills.
B.Sc. in Computer Science, Computer Engineering, Information Systems, or a related field (or equivalent practical experience).
Nice to have:
Experience supporting AI, Machine Learning, or Generative AI workloads, including familiarity with MLOps concepts, AI deployment platforms, or cloud-based AI services.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.
Requirements:
Engineering Foundations:
- Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply.
- Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically.
- Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job.
- Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution.
- Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments.
- Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI.
- Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM).
AI / LLM Expertise:
- Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8744445
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time
We are establishing a new role focused on bridging AI capabilities with our internal DevOps platform. You will build AI-powered tools and services that run on top of the DevOps platform developed by the infrastructure team. This role combines hands-on DevOps/platform engineering work with close collaboration with software development teams, enabling them to build, deploy, and operate AI solutions efficiently, securely, and in alignment with organizational standards. You will act as a technical enabler, helping teams bring AI-driven applications into production while ensuring best practices across architecture, compliance, DevSecOps, FinOps, and AI governance. The role also includes direct contributions to the platform itself.
Your Impact
Enhance DevOps platform capabilities to support AI-based tools and workloads.
Work closely with development teams to enable and support AI application delivery end-to-end.
Assist in designing architecture and production-grade implementation of AI systems.
Lead and enforce DevSecOps practices, compliance requirements, and governance standards for AI solutions.
Develop platform components and internal services as part of the AI infrastructure layer.
Support production readiness, monitoring, performance, reliability, and cost optimization (FinOps).
Serve as a technical interface between multiple engineering teams.
Participate in future on-call rotations.
Requirements:
Your Experience
Strong experience of 5-7 years in DevOps / Platform Engineering roles.
Good understanding of the AI ecosystem and modern AI workflows.
Hands-on familiarity with AI tools such as Claude and other GenAI platforms.
Ability to present a personal AI-related project
Solid understanding of production systems and modern CI/CD practices.
Experience with cloud infrastructure, automation, and deployment pipelines.
Strong communication skills and ability to work across multiple stakeholders.
Nice to have
Exposure to DevSecOps, compliance, and FinOps practices.
Experience building or integrating AI-driven systems in production environments.
Experience building tools or automations using Claude or similar GenAI tools.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8781332
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דיווח על תוכן לא הולם או מפלה
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שליחה
סגור
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior Site Reliability Engineer at our company 911, you'll own the infrastructure that keeps our platform reliable, scalable, and secure - work that directly supports mission-critical 911 systems used by public safety agencies. You'll drive infrastructure-as-code practices across AWS, lead observability efforts through Datadog, and bring modern AI-assisted engineering approaches into how the team builds and operates.
What You'll Do
Own and evolve AWS infrastructure using Infrastructure-as-Code (Terraform / Terragrunt)
Architect and scale AWS environments
Deploy, scale, and manage containerized workloads using Kubernetes and Docker; contribute to HA/DR architecture and platform strategy
Lead deployment and release processes using Argo (reference JD also names Bitbucket, Jenkins as part of the CI/CD toolset).
Define and enforce SLOs, SLIs, and error budgets; drive toil reduction across the platform
Drive full utilization of Datadog for monitoring, dashboards, and alerting across the platform (reference JD also names Prometheus, Grafana as potential observability tooling)
Build self-service internal developer platforms that empower teams to ship faster.
Take end-to-end ownership of infrastructure projects - define success criteria, execute, and measure outcomes.
Partner cross-functionally with engineering teams (e.g., network engineering, Dev owners) on long-term technical planning.
Bring AI-assisted engineering practices (e.g., Claude, MCP integrations) into daily workflows to improve team efficiency
Document work and provide cross-training to peers.
Resolve JIRA tickets across Cloud, CI/CD, deployments, and monitoring.
Requirements:
At least 6 years of experience as a DevOps/SRE engineer in a cloud environment
Hands-on, production-level AWS experience.
Hands-on production experience with Kubernetes and containerization
Experience with Terraform/Terragrunt (or similar Infrastructure-as-Code tools) - required
Strong Bash scripting skills
Deep understanding of SRE principles: SLOs, SLIs, error budgets, toil reduction, blameless post-mortems
Strong incident management / on-call experience
Solid understanding of APIs, microservices, and distributed systems
Demonstrated experience leading a project end-to-end, from defining success criteria through delivery and measurement
Communicates effectively across teams and can drive long-term technical planning
Practical experience with AI-assisted engineering tools (e.g., Claude, Cursor) and MCP-style integrations is a strong plus
Experience building AI/ML infrastructure (model deployment, inference pipelines)-plus.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8796929
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
3 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.
Requirements:
Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals.
Production Experience: Experience building and operating production systems in cloud environments.
Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks.
Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands.
(Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8792284
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