לוח משרות דרושים AI Engineer משרה מלאה

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.

You will play a critical role in adding AI capabilities to our FinOps SaaS platform. Whether it's enhancing user workflows, automating insights, or inventing entirely new product experiences, youll have both the freedom and support to experiment and execute.

We provide a uniquely rich dataset covering the full scope of a companys cloud spend. This expansive data playground offers a powerful foundation for experimentation and insight generation, enabling the development of intelligent, value-driven features.

Responsibilities:
Lead the charge in transforming our product and preparing it for the agentic age.
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.

If youre looking to build something big, solve real problems, and grow fast-wed love to meet you.

You will own AI infrastructure and agentic interaction layer on top of our Data Platform.

The data layer is the product.
The AI layer is the multiplier.
The interaction model between them is the future.

Your responsibility is to design and build:

The AI infrastructure that enables safe, scalable, production-grade AI features

The ability to interact with Data Layer through LLMs and agentic workflows

Guardrails, governance, and system boundaries for AI-driven data access

The foundations that allow AI to be powerful without compromising correctness or trust

our company, a software development company specializing in sophisticated e-commerce solutions, is looking for a motivated, talented, and skilled AI Officer. Our clients include leading brands such as McDonald's, Azrieli, Aroma Israel, Shlomo Group, Meshulam, Htzone, NewDeli, and more. This is a unique opportunity to showcase your talent, work with advanced technologies, collaborate with amazing colleagues, and support major customers.
Responsibilities:

* Monitor AI tools usage across the organization on an ongoing basis
* Ensure compliance with internal policies, procedures, and applicable AI regulations
* Review and approve requests for AI tool usage according to defined criteria
* Identify deviations, risks, and compliance gaps, and recommend corrective actions

As the Product Manager for the AI models of core product offering, you will be responsible for defining and driving its product strategy, requirements, roadmap and delivery.

The product focuses on addressing real-world challenges in drug development by leveraging AI foundation models and multi-omic data to map and predict human immune response.

You will be working closely with our team of Data Scientists, Computational Biologists, Deep Learning Researchers and Engineers.

Location: Ramat Gan, Israel (Hybrid model)

What will you do?

Set the long-term vision and strategy for AI models, ensuring alignment with company goals.
Define product requirements and build a clear, prioritized roadmap for model development and delivery.
Lead benchmarking efforts to evaluate model performance against internal baselines and external best-in-class models.
Collaborate with AI research, data science, engineering, and biologists to translate scientific advances into scalable product capabilities.
Oversee the end-to-end lifecycle of AI models, including data strategy, training priorities, evaluation criteria, releases, and post-deployment monitoring.
Identify, validate, and prioritize high-impact use cases where improved model capabilities create meaningful business or scientific value.
Communicate strategy, progress, and key decisions to leadership and cross-functional stakeholders to drive alignment.

We are looking for a driven and experienced leader to manage a growing interdisciplinary team of LLM Agentic AI Researchers, Computational Biologists, and Immunologists. This teams mission is to build a cutting-edge agentic reasoning system powered by Large Language Models (LLMs), capable of generating structured, biologically grounded sequential explanations based on predictions from proprietary foundation model-trained on hundreds of millions of immune cells. The product the team builds is a pillar of AI strategy, with the potential to redefine the way a drugs mode of action is understood.

Location: Ramat Gan, Israel (hybrid model)

What You'll Do:

Set the Vision - Collaborate with product leadership to transform bold ideas into AI capabilities that impact real-world medical decisions.
Build and Lead the Team - Coach, build and inspire a high-caliber team across LLMs, data science, and Immunology. Cultivate a culture of excellence, curiosity, and execution.
Drive Innovation - Lead from the front-design architectures, write prototypes, and guide technical direction. Lead the team in building agents that reason about biological systems at scale.
Ship Transformative Products - Deliver AI products & solutions that move the needle and its partners - from static biological associations to dynamic, explanatory models of causality.
Showcase Leadership - Represent the team in top-tier scientific conferences and publications, communicating groundbreaking research to the world.

We are looking for an experienced AI Automation Expert who will design, build, and maintain advanced AI driven workflows, internal agents, and process automations across the organization. The ideal candidate has hands on experience with automation platforms such as n8n, Zapier or Make, strong technical understanding of modern AI models and APIs, and a proven record of translating business needs into scalable automated solutions.

This position plays a central role in our digital transformation efforts. You will be a partner with operations, support, engineering, and business leadership to streamline processes, reduce manual workload, and accelerate delivery through smart automation.

Responsibilities

AI and Automation Architecture

Design and implement AI powered automations, including conversational agents, workflow orchestrations, and custom business logic.

Build and maintain automations using n8n, Flowgrammers, and similar workflow tools.

Create structured agent architectures using LLMs, vector databases, and contextual memory.

Develop and maintain reusable automation components and templates.

Process Design and Optimization

Map and analyze existing processes together with relevant stakeholders.

Identify opportunities for automation and propose clear technical solutions.

Implement end to end workflows from data ingestion to final output and quality control.

Ensure security, reliability, and compliance in all automated processes.

Systems Integration:

Connect internal systems such as CRM, ERP, customer support tools, databases, and cloud platforms to automation workflows.

Integrate external APIs including OpenAI, Azure OpenAI, Google Cloud, or vendor specific APIs.

Build bridges between systems that were not originally designed to work together.

AI Agent Development:

Design and deploy specialized agents for operations, sales, customer support, and engineering teams.

Implement context awareness, memory persistence, and custom tool calling for agents.

Optimize agent performance, latency, and accuracy.

Monitoring and Maintenance

Create dashboards and alerting for workflow health and performance.

Troubleshoot failures, scalability issues, and data inconsistencies.

Continuously improve existing automations based on usage and feedback.

It starts with you - an AI Engineering Team Lead responsible for leading a team building production-grade agentic systems. This role combines hands-on technical leadership with people management, ownership of architecture, delivery, and quality across agents, MCP tools, agentic workflows, RAG systems, and evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor a team of AI Engineers building agentic systems and MCP tools.
Own technical direction for agent architectures, workflows, and LLM evals.
Review designs and code; ensure production readiness, reliability, and security.
Drive adoption of frameworks such as LangChain, LangGraph, or equivalent.
Set standards for RAG pipelines, vector databases, and retrieval quality.
Partner with product and platform teams on roadmap, scope, and delivery.
Balance hands-on contribution with people management and execution.
Build a culture of strong engineering practices, measurement, and iteration.

It starts with you - a senior AI engineer focused on building production-grade agentic systems: autonomous agents, MCP tools, agentic workflows, and rigorous evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design and build single- and multi-agent systems with planning, memory, and tool use.
Implement and operate MCP tools and servers with secure schemas and permissions.
Build agentic workflows using LangChain, LangGraph, or equivalent frameworks.
Integrate LLMs via SDKs; manage prompts, structured outputs, and tool calling.
Define and run LLM evals (quality, correctness, latency, cost, regressions).
Add observability and reliability (logging, tracing, retries, state management).
Optimize performance and cost; take systems to production.
Mentor engineers and establish agentic best practices.