לוח משרות דרושים AI Engineer משרה מלאה, לחיפוש זה נמצאו 162 משרות

a global technology organization developing shared platform services and enterprise applications, with a strong focus on reliability, security, and scalability, is looking for a hands-on senior software engineer with a strong focus on ai-powered development, intelligent agents, and process automation. the role combines Full-Stack engineering with building smart tools and automated workflows using technologies such as claude code, helping improve engineering productivity, streamline processes, and reduce manual work.
responsibilities:
use claude code and other ai-powered tools to accelerate coding, testing, debugging, and documentation.
build intelligent agents, internal tools, and automations to optimize workflows and reduce repetitive tasks.
identify opportunities to leverage ai to improve engineering efficiency and operational processes.
develop frontend applications using React, JavaScript, and typescript.
build backend services and rest apis using C # and.net core.
develop automated tests and end-to-end validation workflows.
automate the validation of integrations and high-volume data operations.
integrate ai-driven solutions into existing development workflows and platform services.
collaborate with a globally distributed engineering team to deliver reliable, scalable solutions.

about the company:
the company is an ai-driven platform company focused on improving drug discovery and development by decoding the human immune system.
we combine large-scale single cell immune data, advanced Machine Learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process.
our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. were building this platform thoughtfully and collaboratively, bringing together expertise across biology, ai, engineering, and business.
the company is an equal opportunity employer. we celebrate diversity and are committed to creating an inclusive environment for all employees.
about the role:
we are looking for an ml infra engineer to play a central role in evaluating, and deploying the company's ai models. you will own and evolve the company's benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. this role sits at the intersection of software engineering, model understanding, and applied ai, with broad influence on how models are built, compared, and improved across the organization.
this is not a core algorithmic research role - but rather, a role focused on building out the ml engineering infrastructure for the evaluation and deployment of models.
location: ramat gan, israel (hybrid model)
what will you do?
own & evolve benchmarking - design, build, and maintain the company's benchmarking suite for foundation models and multimodal ai systems.
define core abstractions - create clean, extensible abstractions and apis for datasets, tasks, models, metrics, and evaluation workflows.
develop metrics & evaluations - implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
support model development - work closely with ai scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
bring in new models & baselines - add external and internal models to benchmarks and ensure meaningful comparisons.
explore data when needed - dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
enable rigor & reproducibility - ensure evaluations are consistent, well-versioned, and trustworthy over time.
when you apply for a role at the company, we process your personal data (such as cv, contact details, and professional background) to assess your suitability for current and future roles. your information may be shared internally with relevant employees and stored or processed by trusted service providers, some of whom may be located outside your country of residence. you can read more about how we process data here: company.com/privacy-policy/.

about the company:
the company is an ai-driven platform company focused on improving drug discovery and development by decoding the human immune system.
we combine large-scale single cell immune data, advanced Machine Learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process.
our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. were building this platform thoughtfully and collaboratively, bringing together expertise across biology, ai, engineering, and business.
the company is an equal opportunity employer. we celebrate diversity and are committed to creating an inclusive environment for all employees.
about the role:
we are looking for an ai infrastructure engineer to build the foundation that enables ai agents to reliably access and operate the company's internal systems, including code repositories, pipelines, datasets, and compute infrastructure.
you will develop scalable, secure, and standardized infrastructure for agentic workflows, working closely with computational biology and engineering teams to continuously improve how ai supports research and development.
this is a software infrastructure role, not a scientific modeling role, focused on building the systems that enable ai agents to operate effectively and safely.
location: ramat gan, israel (hybrid)
what will you do?
build agent infrastructure - design and maintain infrastructure enabling ai agents to interact with internal systems, data, and compute.
ensure quality & reliability - establish testing, ci/cd, and evaluation standards for agentic workflows.
implement safety controls - build permissions, approvals, and audit mechanisms for autonomous agents.
drive continuous improvement - monitor agent behavior and usage to improve reliability and performance.
scale agentic workflows - support reliable autonomous and multi-agent operations across teams and users.
optimize efficiency - manage performance, infrastructure costs, and compute utilization.
collaborate across teams - partner with research and engineering teams to enable ai-driven workflows.

to join Research team. You'll help build our core intelligence engine: LLM agents that run cloud security workflows end to end. These agents investigate runtime detections, reason over workload, identity, and cloud context, and drive remediation in production. You'll research new models and agent designs, run rigorous experiments, and ship what works as high-impact features in our platform.
What you will do:
Build LLM-based agents that investigate, triage, and remediate cloud security threats.
Own the path from research to production: prototype new models, techniques, and agent designs, and ship the ones that work.
Train, fine-tune, and evaluate models for security tasks using vast data sources: runtime events, cloud logs, identity, and network activity.
Build and extend our internal AI platform: services, pipelines, evals, and observability.
Collaborate with Security Researchers, Product, and Engineering to turn research findings into production-grade autonomous workflows.

As a member of our ML group, you will research and build AI systems that change how our silicon is designed. Many of these problems are still open: the right way to frame the problem isn't known yet, and the data is scarce or noisy.

We are looking for a strong researcher who enjoys working closely with design teams to turn open-ended questions into well-posed research problems, and who wants to see the results used in real projects. Success in this role means models and agents that measurably improve designed chip metrics (Power, Performance, and Area) and design turnaround. You will join a growing team of AI and software engineers working with our chip design teams.

Responsibilities
Research and develop AI methods for the physical design flow, from floorplanning and placement through routing and timing closure, combining predictive models, optimization, and generative AI.
Design and build agentic workflows that connect LLMs to EDA tools, design data, and internal infrastructure, to automate and speed up tasks such as flow setup, debug, design exploration, and analysis.
Work with design teams to turn open-ended problems into well-defined research questions with clear metrics, baselines, and success criteria.
Develop robust AI methods for limited, noisy, or imbalanced data, leveraging domain knowledge and advanced learning techniques.
Own data end to end: extract useful signal from EDA tool outputs and design databases, validate and clean it, and build datasets and benchmarks where none exist.
Run careful experiments and evaluations for both models and agents, and report clearly what works and what doesn't.
Work with software engineers and design teams to bring promising prototypes into production flows, and improve them based on feedback from real projects.
Help shape new research directions as our work grows, follow the AI and EDA literature, and bring relevant ideas to the team.

Join our Security Autonomous SOC Team as a Principal AI Engineer to transform innovative AI/LLM research into impactful cybersecurity product features. You will leverage and augment our existing infrastructure, including BI systems and CI/CD pipelines, to design, develop, and deploy advanced LLM and Agentic capabilities. Your expertise in software development, AI engineering, and modern LLM technologies will directly drive the evolution of our security operations. By building robust, production-ready AI solutions, you will make a tangible difference in protecting our digital world against complex threats.
Key Responsibilities
Design and build Agentic security solutions to improve detection, response, and remediation capabilities.
Architect, implement, and optimize end-to-end LLM pipelines ensuring scalability from data ingestion to deployment.
Develop and deploy AI agents leveraging LLMs to automate complex security decision-making tasks.
Integrate LLM APIs and fine-tune models for specific cybersecurity use cases.
Transform promising AI and LLM research concepts into mature, robust, and scalable production-ready features.
Augment established BI data systems and CI/CD pipelines to support advanced AI development and experimentation.
Develop specialized tools and frameworks extending infrastructure to support AI-driven security research and remediation.
Collaborate with cross-functional teams to integrate AI innovations into customer-facing XDR, EDR, and SOAR platforms.

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 company 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.

We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today.
Key Responsibilities
Develop internal AI-powered products and tools used by teams across our company to work faster and smarter.
Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams.
Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows.
Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development.
Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption.
Work hands-on with the most advanced AI development tools and shape how the company uses them.

Morning is looking for a Senior Software Engineer with a builder mindset and a strong backend orientation — someone who enjoys taking ideas from concept to production, working across different parts of the stack, and doing whatever it takes to build great products. At Morning, engineers go beyond traditional role boundaries, taking ownership of solutions end to end rather than handing work off between specialized teams. We value people who are comfortable figuring things out, learning new technologies, and using AI tools to expand what they can build. You'll join our Delivery team, working on both existing products and new features. What you'll do
* Build and ship new features and improve existing products, taking ideas from initial problem-solving through to production.
* Work across the stack and beyond traditional engineering boundaries, taking a hands-on approach to solving problems and delivering complete solutions.
* Use AI-powered development tools extensively to explore solutions, write and improve code, debug issues, and accelerate development.
* Take ownership of the quality and reliability of what you build, critically evaluating AI-generated code and validating solutions before shipping.
* Explore new technologies and approaches to find better ways to build and deliver products. Why join Morning? Our customers rely on us to manage their financial data, so quality, reliability, and trust matter. We believe great engineers shouldn't be limited by rigid role boundaries. Our team takes a hands-on, end-to-end approach to building products — combining engineering, AI tools, experimentation, and whatever skills are needed to turn ideas into reality. You'll have room to take ownership, experiment, and make a meaningful impact, with the opportunity to see your work reach customers without long development cycles.

Advantages:

* Experience working with Databricks or Spark.
* Experience in fintech or other regulated environments.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.

Key responsibilities

Lead a team of data scientists, data engineers and product analysts

Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation

Drive excellence, code quality, and best development practices

Provide technical direction and hands-on guidance for complex AI systems

Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences

Ensure AI solutions are safe, scalable, observable, and continuously improving

Lead initiatives around product data analysis and experimentation

Analyze user interactions with product features to improve accuracy, UX, and business impact

Partner with product teams to define metrics, dashboards, and experiments that guide product improvements

Design system architectures for AI-enabled applications at scale

Evaluate and select technologies for AI platforms and data pipelines

Guide the development of prompt engineering frameworks and centralized prompt management

Ensure robust monitoring, evaluation, and feedback loops for AI outputs

Translate product and business goals into technical roadmaps and execution plans

Drive alignment between AI capabilities and measurable product outcomes

We are seeking a highly skilled and motivated Senior Software Engineer GenAI to join our growing R&D team. In this role, you'll design, develop, and scale our next-generation backend platform, AI-driven workflows, and GenAI applications. You'll work with modern cloud technologies and LLMs to build resilient, high-performance systems while contributing to architecture, technical leadership, and mentoring.

This role is ideal for an experienced backend engineer who enjoys solving complex technical challenges, building scalable systems, and working with cutting-edge AI technologies.

Key Responsibilities

Design and develop scalable backend services using Python.
Build resilient distributed systems, microservices, and AI-driven workflows.
Integrate Large Language Models (LLMs) using AWS Bedrock and other AWS services.
Design and implement event-driven architectures and modern APIs.
Optimize databases, search capabilities, and caching strategies to support high-performance applications.
Contribute to cloud infrastructure, CI/CD pipelines, and observability practices.
Collaborate with Product, Data Science, and Engineering teams to deliver scalable solutions.
Provide technical leadership through architecture discussions, mentoring, and hands-on development.

As an AI Engineer at Glow, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive Glow's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.

This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.

WHAT YOULL DO

End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.

Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.

Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.

Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.

Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

We're building a new orchestration platform for AI datacenters-software that turns a complex, multi-vendor stack of compute, networking, and accelerators into something customers can deploy, operate, and optimize with confidence.
You'll join a small, growing engineering team where every engineer ships. In this hands-on development role, you'll build backend services, contribute to system design, and own features from implementation through production, working closely with experienced engineers.
If you enjoy solving challenging engineering problems, building new products, and seeing your work run at scale in real AI datacenters, this role is for you.
What You'll Do
- Build and maintain core services and features for an orchestration platform spanning compute, networking, and accelerators.
- Translate customer requirements into APIs, workflows, and data models in collaboration with the team.
- Deliver features end-to-end, from prototyping and implementation to testing, deployment, and production support.
- Write reliable, maintainable code and contribute to shared libraries, automated tests, and CI/CD pipelines.
- Contribute to design discussions and make practical implementation tradeoffs around performance, reliability, and simplicity.
- Participate in code reviews, share knowledge, and help improve engineering practices.
- Troubleshoot issues and improve service performance, observability, and operational readiness.