דרושים » הנדסה » AI Engineer

What Were About
we are a fast-growing startup at the forefront of application security. Our cutting-edge platform is designed to help development teams build secure software quickly, enabling them to move faster while managing risks. As pioneers in the AppSec space, were shaping the future of secure software development in the AI era. If you're looking for an exciting opportunity to make a significant impact and grow with a passionate team, we are the place to be.
About the Team
Our team is at the forefront of agentic AI - both within our company and across the broader Application Security space. We lead the development of AI-powered, agentic security capabilities within our ASPM product, driving innovation from early experimentation all the way to production, deployment, and continuous monitoring.
As a cross-functional team, we specialize in turning cutting-edge Machine Learning, Data Science, and agentic AI into scalable, real-world solutions that power our companys platform.
What You Will Do
Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, data scientists, and analysts.
Design, build, and optimize end-to-end AI-driven features and agentic workflows - from experimentation to validation and deployment (using Python and C#).
Develop scalable backend services to support production-grade agentic AI features.
Build and improve solutions powered by LLMs, AI agents, multi-agent systems and generative AI frameworks.
Evaluate agentic architectures and models performance, and contribute to monitoring, reliability, and continuous improvement in production.

We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

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

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

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

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

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

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

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

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

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

Develop proof-of-concepts for new features.

We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.

We are looking for a Senior AI Engineer to join a strong and dynamic AI Engineering team. We are the focal point for AI initiatives, striving to constantly bring innovation and leverage AI capabilities across all company teams and products.
Today, AI is central to how we operate, across the entire organization. It allows us to move fast and release features at a rapid pace, empowers non-technical Forterians to utilize AI tools for increased efficiency, and provides the backdrop for much of the innovation currently occurring in the company.
If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position.
Why should you join us?
This is a great opportunity to be at the cutting edge of the AI revolution, helping to shape and build the AI platform for the future. Together, well build infrastructure for autonomous and interactive agents, enact AI guardrails and evaluation frameworks to ensure performance and safety, and implement state-of-the-art
AI and Agentic patterns.
This role presents a unique opportunity to enter the AI domain. For those with some experience in AI infrastructure, it offers the chance to grow within a team that is evolving us from the AI experimentation phase to building and leveraging AI-powered products.
What you will be doing:
Design, build, and maintain reusable AI capabilities - including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes our vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard our value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across to accelerate AI adoption and productization efforts.

We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.
You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.
Architect and implement distributed services that power AI-driven applications.
Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.
This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.
Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

The Falcon Cloud Security team is looking for a hands-on Engineering Manager / Team Lead to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will lead a team of talented engineers while remaining deeply technical, helping architect and build autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments.
As a player-coach, you will help shape the "brain" of our cloud security platform, guiding both the people and the technology that leverages large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale.

What You'll Do:

Lead & Grow a Team: Manage, mentor, and develop a team of backend engineers, fostering a high-trust, high-performance culture. Conduct regular 1:1s, support career growth, and drive hiring to scale the team.

Stay Hands-On: Remain an active technical contributor - designing, reviewing, and writing production-quality code alongside your team. Lead by example and maintain a strong engineering presence.

Design & Architect: Drive backend engineering efforts to build autonomous agentic frameworks, guiding the team from rapid prototypes to large-scale production applications.

Develop Core Logic: Contribute to and oversee the development of decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams.

Data Integration: Guide the development of high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning.

Scale Systems: Architect and oversee distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation.

Drive Cross-Functional Collaboration: Partner with Product, Design, and peer engineering teams in a "startup-like" environment to define and deliver new platform capabilities with speed and quality.

Raise the Bar: Champion engineering excellence, new technologies, and best practices across the team and broader engineering organization.

As a Senior Developer, youll join our Product Team and play a key role in architecting and developing AI-driven building operating system. Youll work with the team to plan, shape, and build platform components, AI workflows, and new product features. You should feel comfortable collaborating in a product squad and be excited about the new era of AI-native SDLC, using coding agents to move the needle independently while keeping productivity and simplicity in mind.

About you

An ideal candidate is humble and open-minded, while staying skeptical and willing to challenge assumptions. You have strong full-stack engineering skills and experience reasoning about complex systems, evolving architecture, and the importance of collaboration, communication, and product sense. You excel at working independently and as part of a team, and you feel comfortable asking for help when you get stuck.

Responsibilities

Plan, design, and ship agentic workflows that automate operational processes with human oversight built in.
Work cross-functionally with product, design, operations, and business teams to deliver AI features that solve real problems.
Own feature development end-to-end: from ideation and discovery, through spec writing, development, testing, launch, and iteration.
Push the limits of coding agents to increase developer velocity and democratize development for non-coders.

Required Machine Learning Engineer - AI Coding Agents & LLM Infrastructure
Tel Aviv
Full-time
A bit about us:
We are redefining how software gets built. Trusted by over 1M+ developers, we build AI-first developer experiences powered by state-of-the-art coding agents and code reasoning models. With support for 30+ programming languages and 15+ IDEs, our platform is pushing the limits of LLM-based software engineering - enabling teams to design, write, review, and ship code faster than ever. Were committed to advancing code-native AI models, multi-agent systems, agent orchestration frameworks, memory, and autonomous dev tooling to empower developers at every step of the software lifecycle.
Were growing fast, and our team is passionate about pushing AI engineering to new heights - solving complex problems in LLM training, inference optimization, reasoning, and agent orchestration at scale.
About the Role:
As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code models-optimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.