דרושים » AI » AI Research Engineer

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 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 featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith 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.

As a Senior AI Engineer in the Clinical AI domain within our Data & AI group, you will play a critical role in designing, building, and scaling cutting-edge machine learning and LLM-based systems that power our AI-first healthcare experiences. Your work will drive capabilities in clinical risk prediction, conversational agents, and personalized health management tools.

You will take technical ownership of key projects, lead the development of scalable AI systems, and collaborate closely with cross-functional teams spanning product, data science, and engineering. In essence, you will help shape the future of AI in a high-impact, healthcare-focused environment.

Responsibilities:
Lead the technical design, development, and deployment of robust machine learning and LLM-based applications.
Architect and implement scalable systems for conversational agents, risk models, and clinical workflows.
Collaborate with data scientists and product managers to turn research and user insights into production-ready AI solutions.
Contribute to advanced prompt engineering, retrieval-augmented generation (RAG), and agent orchestration efforts.
Design and implement robust evaluation, testing, and monitoring strategies for AI models in production.
Integrate real-time data from mobile apps, wearables, and clinical sources into AI pipelines.
Investigate emerging AI technologies, evaluate their applicability, and recommend their integration into our systems.

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge.

Were seeking an experienced AI/ML Platform Engineer to join our Foundations team, the group behind our next-generation GenAI platform powering innovation across the company and beyond. This team is building scalable, high-performance AI systems for both internal users and external customersdesigned to run seamlessly across cloud and on-premise environments using the latest advancements in hardware. In this role, youll lead efforts in distributed training, inference at large scale, resource optimization, and robust model lifecycle management using MLOps best practices. Your work will be critical to accelerating research, supporting production-grade AI infrastructure, and driving the development of our internal AI ecosystem.

Responsibilities
Architect and build scalable ML infrastructure for training and inference workloads across heterogeneous compute environments (on-premise and cloud).
Design and implement distributed systems to support model lifecycle management from data ingestion and preprocessing, to training orchestration and deployment.
Optimize performance and cost-efficiency of large-scale model training and serving pipelines using technologies like Ray, Kubernetes, Spark, and GPU schedulers.
Collaborate with AI researchers, data scientists, and product teams to understand their workflows and translate them into reusable platform services and APIs.
Drive adoption of best practices for CI/CD, observability, and reproducibility in ML systems.
Contribute to the long-term vision and technical roadmap of the ML platform, ensuring it evolves to meet the growing demands of AI across the company.

A global leader in hybrid cloud security. We bring a new approach that uses the attackers perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. The platform enables companies to rapidly prioritize and respond to cyber risks affecting their business-sensitive systems.
We are seeking a highly skilled and motivated backend Engineer with a Generative AI orientation to join our Infra team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities across our product line. This platform will handle cross-team concerns, such as prompt management, model access, data filtering, logging, and monitoring, centrally, so individual teams can focus on their own business-specific logic. As a backend Engineer with a Generative AI orientation, you will be instrumental in designing, developing, and implementing the core services of this foundational AI Platform. You will build components that enable our development teams to quickly innovate with AI while adhering to high standards for quality, cost-effectiveness, and compliance. Responsibilities:
* Develop and maintain a centralized microservice that handles all AI model interactions.
* Build shared services and libraries to maximize development speed and cost-efficiency for AI based features/systems across the company
* Setting the tone in the fields of automatic testing strategies and CI/CD for AI components, prompt management, and more.
* Define and enforce best practices for model governance, security, and compliance.

We are looking for an experienced Software Engineer with GenAI/ML knowledge to join our AI/ML Applications team. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and GenAI pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model/agent deployment both in cloud environments and on-premise. Youll optimize and implement workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust GenAI systems.
Optimize system performance, including robustness, scalability, communication protocols and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

Were seeking an AI Innovation Security Researcher to serve as the critical link between our AI development team and our security experts. In this role, you will:

Translate real-world security challenges into AI-driven solutions
Shape prompt strategies and model workflows for security use-cases
Contribute to AI system developmenthelp architect, prototype, and iterate on models and pipelines
Design and execute rigorous benchmarks to evaluate the performance of security-focused AI tools
Your work will power capabilities such as automated exploitability checks for SAST/SCA findings, AI-guided remediation of container vulnerabilities (e.g. Dockerfile misconfigurations, unsafe downloads), and detection/analysis of data leaks. Youll also help amplify our thought leadership by authoring blogs and delivering conference talks on cutting-edge AI-security topics.

Key Responsibilities

Research & Benchmarking

Define evaluation frameworks for AI models tackling security tasks
Build test suites for exploitability analysis (e.g. proof-of-concept generation, severity scoring)
Measure and report on model accuracy, false-positive/negative rates, and robustness
AI Collaboration & Development

Work with ML engineers to craft and refine prompt templates for security scenarios
Contribute to model architecture design, fine-tuning, and deployment workflows
Investigate model behaviors, iterate on training data, and integrate new AI architectures as needed
Security Expertise & Tooling

Apply deep knowledge of static and software composition analysis (SAST/SCA)
Analyze container build pipelines to identify vulnerability origins and remediation paths
Leverage vulnerability databases (CVE, NVD), threat modeling, and risk assessment techniques
Content Creation & Evangelism

Write technical blog posts, whitepapers, and documentation on AI-driven security solutions
Present findings at internal brown-bags and external conferences
Mentor teammates on AI security best practices

As our company continues to grow, an exciting opportunity awaits a dynamic individual to join our R&D team as an AI Engineer. We are seeking a highly skilled AI Engineer with expertise in LLMs, computer vision, NER, statistical modeling, and classic ML. The ideal candidate will have strong backend software engineering skills, advanced proficiency in Python, and extensive experience in the end-to-end development, deployment, and maintenance of AI-driven systems. This role requires a team player with a can-do attitude who thrives in a collaborative environment, bringing innovative ideas from concept to scalable, high-quality products.

Responsibilities:
Design and develop LLM-powered AI solutions (e.g., intelligent agents, semantic search, document understanding) for production environments.
Implement integrations with multiple data sources and APIs to extend AI capabilities and automate workflows.
Build and optimize end-to-end AI pipelines, from data ingestion and preprocessing to model deployment and monitoring.
Collaborate with product, data, and UX teams to ensure solutions address real business needs and deliver measurable value.
Continuously evaluate, fine-tune, and improve model performance and scalability.