דרושים » AI » AI Security Engineer

Were looking for a Generative AI Developer to join our forward-thinking engineering team. This role is perfect for someone with a passion for cutting-edge AI, a strong software engineering background, and the creative spark to identify and implement novel use cases within our product.

What youll do:
Design, build, and deploy generative AI-powered features across our product.

Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs

Prototype and validate new AI use cases quickly and iterate based on internal and external feedback

Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production

Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).

Live in the future and track new innovations and paradigms in this fast-evolving field, and identify opportunities to integrate them into the product

Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs

Optimize model performance, inference time, and cost efficiency within AWS infrastructure

property management software built for speed and the smart choice for people who take growth seriously. With offices in Miami, New York City, and Tel Aviv, were a global company helping property owners and managers move faster, scale smarter, and get real support, real fast.
Were proudly People First. Thats why were a Certified Great Place to Work, recognized by Forbes as one of Americas Best Startup Employers in both 2024 and 2025, and earn top ratings on Glassdoor.

Mission
seeking an experienced AI Engineer to join our fast-growing team. In this role, you will design, train, and deploy AI models to solve real-world problems. You will work closely with cross-functional teams, including software engineers, DevOps engineers, and product managers, to integrate intelligent features into our platform and services.

Responsibilities
LangChain/LangGraph Development: Build and maintain modular, scalable LLM-powered agents and tools using LangChain and/or LangGraph.
Retrieval-Augmented Generation (RAG): Implement RAG-based solutions to improve AI responses using external knowledge bases.
API & Backend Integration: Work with software engineers to integrate AI systems into backend infrastructure and expose them via APIs.
AI Agent Development: Design, build, and deploy autonomous AI agents that can reason and execute multi-step tasks using LLMs, tools, memory, and APIs.
Experimentation & Evaluation: Continuously refine models using A/B testing, human feedback loops, and AI evaluation metrics.
Stay Updated: Keep up with the latest LLM advancements and best practices in the AI industry.
Product applications: Apply LLMs and agents to real-world scenarios that solve meaningful user problems.
Product implementation: Work closely with the product team to ensure that delivery is aligned with expected product requirements
Response validation: Implement a process to ensure accurate KPI measurement and consistent, expected outcomes.
Typescript Integration: (Preferred) Help implement and maintain AI modules and integrations using Typescript-based stacks.

Were looking for an experienced MLOps / DevOps Engineer to design and manage the infrastructure powering large-scale machine learning systems. Youll be responsible for deploying GPU-heavy models (including LLMs) on cost-efficient, production-grade infrastructure, supporting both ML workflows and application artifact delivery.

Youll work with cutting-edge technologies like vLLM, Triton, SageMaker, ClearML, Karpenter, KEDA, and EKS, ensuring the right balance between performance, scalability, and cost.



What Youll Do

Deploy and manage LLMs and deep learning models using vLLM, Triton Inference Server, and custom API endpoints.

Build and maintain GPU-aware autoscaling clusters using AWS EKS, Karpenter, and KEDA, optimizing for cost-efficiency and performance.

Develop CI/CD pipelines using Jenkins and GitHub Actions to automate ML model delivery and application deployments.

Orchestrate training, fine-tuning, and inference jobs on AWS SageMaker and ClearML, with support for experiment tracking, versioning, and reproducibility.

Support backend teams in deploying app artifacts and runtime environments; implement rollback and release strategies.

Integrate observability tooling (e.g., Prometheus, Grafana, ELK, or OpenTelemetry) for both infrastructure and model performance.

Collaborate with SREs to enforce high availability, disaster recovery, and incident response procedures for mission-critical AI services.

Were looking for a hands-on AI Architect to join our Platform infrastructure (Gen AI applications team) where you'll have the unique opportunity to collaborate with our strategic technical leadership and the development of next-generation technologies for modern software release management, driving the industry forward.
As an AI Architect you will...
Design, develop, and implement various ML and AI-based solutions to address business needs and objectives
Collaborate with key organizational stakeholders to understand AI requirements and design end-to-end AI solutions
Explore and experiment with novel ML and AI techniques and architectures to drive innovation
Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness
Ensure the scalability and reliability of LLM-based system architectures
Provide technical guidance and mentorship to development teams on AI and ML technologies and practices
Influence the AI priorities of the company. Your decisions will shape our future direction in AI, and have a significant impact on our AI initiatives.

We are seeking for an experienced, hands-on Senior ML / AI Engineer to join the Generative AI applications platform group and lead the implementation and integration of AI/ML solutions.
As a Senior ML / AI Engineer you will...
Understand the challenges our users face and how to integrate and implement AI/ML solutions to solve those challenges
Work with stakeholders such as engineers, Product Management, and analysts to translate business problems to technical requirements and solutions
Design, develop, and implement POCs for ML models and GenAI solutions to address business needs and objectives
Provide technical guidance and mentorship to development teams on AI/ML technologies and practices
Build ML capabilities from ideation to production.

Were looking for a Product Manager to lead LLM Infrastructure - a foundational role driving the development of systems that enable smarter, AI-powered decision making across the marketplace.

As the PM for LLM Infrastructure, youll shape the capabilities that turn unstructured data into structured, explainable, and actionable insights. Youll work closely with ML engineers, data scientists, and product leaders to design scalable tools and frameworks that support use cases across personalization, matching, search understanding, trust and safety, and more.

Your mission will be to build reliable and extensible LLM-based systems that serve as core building blocks for future-facing product innovation.

What am I going to do?
Define the product vision and roadmap for LLM infrastructure, aligning with long-term company strategy and cross-team needs.
Lead the development of scalable systems that extract meaning.
Structure from conversational and behavioral data.
Drive adoption of LLM capabilities across by building unified APIs, shared frameworks, and streamlined integration pipelines.
Partner with engineering, data science, and research teams to deliver high-quality infrastructure that powers AI-native product experiences.
Collaborate on system design and architecture decisions to ensure alignment between technical solutions and product scope.
Ensure reliability, scalability, explainability, and performance in all LLM-based systems.
Manage technical complexity and connect infrastructure efforts with clear business value.

Were looking for a hands-on, product-minded AI professional to help us tackle real-world cybersecurity challenges using existing LLM technologies (like OpenAI, Claude, Bedrock, and more). Youll be part of the Product & AI team, working closely with product managers, engineers, and internal stakeholders to translate problems into smart, working AI-powered solutions.
This is not a researcher or data science role. Its a solution-driven, execution-oriented position for someone who knows what LLMs can do, and how to make them deliver value today.

Key Responsibilities:
Design AI-powered solutions using off-the-shelf tools and APIs (prompting, chaining, agents, etc.)
Collaborate with product and R&D teams to deliver working features and PoCs
Own the how of AI: from idea to prototype to functional integration
Track AI industry trends and apply relevant ideas and tools
Act as a cross-functional bridge between product, tech, and innovation

What We Offer:
A product-driven AI role with real-world impact
A collaborative, innovation-focused environment
The opportunity to shape how GenAI powers critical systems in the automotive cybersecurity space

were on a mission to help engineering teams build secure software, faster.
Were looking for an AI Engineer with a background in agentic AI solutions to join our growing team and push the boundaries of what modern AppSec tooling can do.

Responsibilities:
Design and implement Retrieval-Augmented Generation (RAG) pipelines tailored to security use cases.
Develop robust prompt-engineering strategies to enable dynamic threat detection and remediation.
Construct evaluation frameworks for assessing model performance and behavior in real-world AppSec scenarios.
Integrate large language models (LLMs) into production environments to enable autonomous task handling and decision-making.
Collaborate closely with engineering, product, and security teams to translate AI research into product innovation.

We're looking for a AI Research Scientist to join us
WHAT YOULL DO

Develop and research novel AI models, focusing on transformers and deep learning. Lead mid- to long-term projects aimed at advancing AI-driven features in the cybersecurity domain for products.
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay informed about cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions accuracy, efficiency, and scalability.
Collaborate with engineering teams to design, build, and maintain production pipelines. Work closely with the Security Research and Product teams to define research goals.
Publish research findings and AI thought leadership content and present at leading conferences such as NeurIPS, ICML, or CVPR.

We are seeking an experienced Data Scientist with a strong background in AI engineering to join our AI Platform team. This role focuses on developing and fine-tuning advanced machine learning models, including LLMs, to support various product teams across . As a member of the AI Platform team, you will collaborate with cross-functional teams to build scalable, efficient, and robust AI solutions that serve diverse business domains.

What am I going to do?
Take leading roles in foundational AI projects across : developing and fine-tuning LLMs, building reusable components for generative AI, supporting real-time predictions, and enabling streaming data utilization across online models.
Provide advanced Data Science and AI Engineering solutions end-to-end - from research and prototyping to robust production-grade implementations.
Own the design, training, and evaluation of models tailored for tasks like summarization, classification, semantic matching, personalization, and more.
Drive innovation by exploring new model architectures, training techniques, and fine-tuning strategies aligned with business needs.
Lead and mentor other team members, setting high standards for technical excellence and knowledge sharing.
Continuously identify new opportunities to evolve the platforms capabilities and streamline how AI is built and adopted across .