דרושים » הנדסה » AI Engineer

We are seeking an experienced Generative AI Engineer to join our AI squad
Key Responsibilities:
GenAI Development & Implementation:
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation:
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

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 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

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.

Together with our customers, were helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary
Product Manager - Generative AI (Prompt)
Dynamic Yield, were on a mission to shape the future of personalization. As a global leader in experience optimization, we help hundreds of brands deliver tailored content and product recommendations to millions of users in real time.

We are now hiring our first Product Manager to lead the development of GenAI-powered experiences. Youll work across multiple product lines to design and implement production-grade prompt architectures, embed AI agents into the user journey, and scale experimentation with cutting-edge LLM tools.

Product Team Member Prompt Engineer

This role blends hands-on AI development with product integration strategy. Youll collaborate with product managers and engineers to design, evaluate, and iterate on generative AI solutions including multi-step prompt chains, agent workflows, and LLM selection frameworks. Your work will shape how personalization evolves across the Dynamic Yield platform.

All About the Role
Bring experience delivering products in SaaS startups or enterprise environments, with a deep understanding of market dynamics, customer needs, and the competitive landscape.
Design and refine context and prompt architectures (e.g., few-shot, chain-of-thought, tool use) that drive our LLM-powered features
Select and evaluate models, frameworks, and orchestration tools (e.g., OpenAI, Claude, LangChain, RAG)
As part of the product team you will collaborate cross-functionally with developers, UX, BI, and Product Marketing to ensure product success across the board
Collaborate with engineers to implement scalable agent-based workflows and integrate GenAI into the product
Partner with Product Managers to define user-facing use cases and influence product direction with AI capabilities
Develop internal tooling and evaluation frameworks to test prompt quality, model behavior, and UX alignment
Act as a thought leader on prompt best practices, model safety, and responsible AI design across product squads

We are looking for a passionate and experienced Hands-On Tech Lead to join our Technology Consulting department and lead the design and implementation of cutting-edge Generative AI solutions. This role is ideal for someone who thrives at the intersection of technology leadership and hands-on development, and who is excited to shape the future of AI-driven innovation for top-tier clients.
Key Responsibilities:
Lead the technical design, architecture, and implementation of Generative AI solutions (e.g., LLMs, multimodal models, RAG pipelines, fine-tuning, prompt engineering).
Collaborate with cross-functional teams including data scientists, software engineers, consultants, and business stakeholders.
Stay up to date with the latest advancements in GenAI and translate them into practical, scalable solutions.
Guide and mentor junior developers and AI engineers.
Work closely with clients to understand business needs and translate them into technical requirements.
Ensure high-quality delivery, performance, and security of AI applications.

We are seeking a talented Software Development Leader with a strong background in Large Language Models (LLM) and GenAI engineering.
This is a unique opportunity to work with US clients and engage in global projects, leveraging your extensive skills in generative AI tools.
As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative projects. In this role you will:
Lead development of robust, efficient, and scalable Python code, ensuring adherence to best practices in software engineering and optimization for high-performance applications.
Utilize GenAI engineering tools such as LangChain, RAG, Agents, and Vector Database for implementation and optimization.
Stay updated with AI protocols and standards and ensure their correct application in projects.
Collaborate with other teams and team members to understand requirements and develop solutions.
Analyze complex problems, identify and define the computational requirements to solve them.

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 are now hiring our first Prompt Engineer to join the Product team and lead the development of GenAI-powered experiences. Youll work across multiple product lines to design and implement production-grade prompt architectures, embed AI agents into the user journey, and scale experimentation with cutting-edge LLM tools.

Product Team Member Prompt Engineer

This role blends hands-on AI development with product integration strategy. Youll collaborate with product managers and engineers to design, evaluate, and iterate on generative AI solutions including multi-step prompt chains, agent workflows, and LLM selection frameworks. Your work will shape how personalization evolves across the Dynamic Yield platform.

All About the Role

Design and refine prompt architectures (e.g., few-shot, chain-of-thought, tool use) that drive our LLM-powered features

Select and evaluate models, frameworks, and orchestration tools (e.g., OpenAI, Claude, LangChain, RAG)

Collaborate with engineers to implement scalable agent-based workflows and integrate GenAI into the product

Partner with Product Managers to define user-facing use cases and influence product direction with AI capabilities

Develop internal tooling and evaluation frameworks to test prompt quality, model behavior, and UX alignment

Act as a thought leader on prompt best practices, model safety, and responsible AI design across product squads