לוח משרות דרושים מהנדסים עבודה היברידית, לחיפוש זה נמצאו 240 משרות

we are looking for a Developer Experience Engineer.
Own the surfaces developers touch every day - the riven CLI, our SDKs, the Electron desktop IDE, and the docs. Make the path from zero to a deployed app feel effortless.

Design and build the infrastructure and interfaces that power context-AI platform, owning features end to end, from technical design through production.
What you'll do:
Design, implement, and scale data-intensive processing pipelines and core platform architecture.
Develop and scale the backend infrastructure behind our context-AI capabilities and production apps.
Build and maintain intuitive interfaces for complex data visualization and interaction.
Optimize performance across distributed systems, databases, and cloud architectures.
Own the full feature lifecycle: technical design, deployment, and monitoring.
Lead technical initiatives, shape the product roadmap, and mentor junior engineers.

we are looking for a Senior Full Stack Engineer to join our Engineering team. In this role, you will lead the design and development of end-to-end features across our gifting platform, with a strong focus on backend architecture. Youll play a key role in shaping scalable systems, driving technical decisions, and delivering high-impact solutions in a fast-growing, cloud-based SaaS environment.
Working with modern technologies such as React, Node.js, TypeScript, Serverless architecture, and Kafka, you will collaborate closely with product, design, and data teams to build reliable, performant, and user-centric experiences. You will also help evolve our engineering standards, development processes, and use of emerging tools-including AI-to improve team productivity and product quality.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.

What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our company core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements
Design and oversee API strategies, event-driven architectures, and middleware patterns that support scalable AI feature delivery - including agentic workflows, intelligent data transformation, anomaly detection, and natural language interfaces layered onto ERP and CRM data
Collaborate with Engineering during build phases, conducting architecture reviews, providing hands-on guidance, and resolving complex technical blockers
Define non-functional requirements - latency, security, auditability, model drift monitoring - for AI components embedded in mission-critical business processes
Establish MLOps and LLMOps practices appropriate for our enterprise environment: model versioning, observability, and rollback procedures for production AI workloads

We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv.
This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company.
What Youll Do:
Design and build reusable AI platform capabilities used across multiple products.
Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities.
Design and build internal AI platforms such as organizational knowledge (Brain), AI developer tools, autonomous engineering workflows, and shared AI services.
Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform.
Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities.
Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment.
Build and operate production AI services using modern cloud-native technologies.
Improve the reliability, scalability and observability of AI systems.
Define engineering standards, reusable patterns and best practices for AI development across engineering teams.
Lead technical proof-of-concepts and drive adoption of innovative AI technologies.
Mentor engineers and provide technical leadership on complex AI initiatives.

we are looking for a MLOps Engineer.
As an MLOps Engineer, you will work at the intersection of backend engineering and machine learning, building the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features used by hundreds of thousands of families.
What you'll be doing -
Build Production AI Systems - Design and implement backend services and end-to-end AI solutions that integrate Deep Learning models, Computer Vision algorithms, and GenAI into real features.
Power Experimentation and Validation - Contribute to the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Develop Data Pipelines - Build and maintain scalable data pipelines and big-data solutions that feed AI capabilities reliably and with an eye on cost and scale.
Own What You Ship - Take features end-to-end within your squad, from planning and design through implementation, deployment, and monitoring in production.
Cross-functional Collaboration - Work closely with the Algorithms and Data teams to tackle complex, real-world problems, helping translate research into shippable, maintainable systems.
Backend Guild Engagement - Actively contribute to a backend guild that drives Software Engineering and System Design best practices, guidelines, and standards across the R&D team.

we are looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:

we are looking for a Senior Backend Engineer with a strong passion for AI and intelligent systems to join our growing R&D team.
In this role, youll be building the backend foundation that powers our AI-enhanced security analytics, autonomous detection, and real-time decisioning systems. Youll work closely with AI engineers, product, and security experts to bring agentic intelligence into runtime platform - transforming how modern apps defend themselves.
Youll architect and implement services that scale to massive volumes of runtime data, integrate large language models (LLMs), and support RAG-based workflows for contextual understanding and response.
Youll Be Great For This Role If You Love To:
Design and build scalable, resilient backend services that power AI-driven runtime security platform.
Integrate LLMs and agentic AI components into production environments to enable autonomous detection and remediation capabilities.
Design evaluation frameworks for measuring model performance and reliability in real-world conditions.
Develop Retrieval-Augmented Generation (RAG) pipelines tailored to application security data.
Own backend architecture decisions - from data modeling to performance optimization - across Node.js, Python, and cloud-native environments.
Contribute to our infrastructure, leveraging CI/CD, Kubernetes, Docker, and modern observability practices.
Mentor peers and help shape AI engineering culture.

We're looking for an AI Tech Lead to own that standard across three surfaces:
The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter - with evaluation, observability, and cost control built in rather than bolted on.
Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere - engineering, research, product, GTM - through tooling, patterns, and teaching.
The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public.
This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain i

we are looking for a Senior AI Agents & Full-Stack Engineer.
What You'll Do:
Build advanced AI agent systems for creative and marketing workflows
Design and implement scalable backend services in Python
Develop frontend experiences using React and TypeScript
Work closely with AI researchers, product leaders, and designers
Help shape the architecture and direction of a new product from its earliest stages

Youll collaborate with expert colleagues around the globe to solve problems most people will never even know exist!

Youll be part of building unique solutions shaped by real investigative methodologies, enabling our customers to identify, investigate, visualize and prevent criminal, terror and security threats worldwide.

These solutions are used by law enforcement, national security, and national and military intelligence agencies in almost 100 countries to turn massive, diverse data into clear, actionable intelligence for a safer world.

You will:
Research and develop advanced algorithms for signal processing and communication systems.
Design and implement communication protocols and direction-finding (DF) algorithms using MATLAB, Python, and C/C++.
Translate theoretical concepts into real-world solutions, from initial prototype to field-tested, production-ready systems.
Stay ahead of the curve by reviewing and applying the latest academic and industry research.
Collaborate with multidisciplinary teams to integrate your work into innovative intelligence platforms.