AI Engineer

12/08/2026

Data Scientist

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a talented and motivated Data Scientist for a temporary position to support our growing data, analytics, and AI automation needs. This role focuses on turning large volumes of data into models, insights, and intelligent automation - combining classic data science (statistical analysis, feature engineering, machine learning) with the emerging Agentic AI stack (LLMs, MCP, agent orchestration). You will work closely with data engineers and internal teams to prototype and productionise models, build LLM-powered agents and workflows, and support the integration of AI capabilities across the organization.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.

Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.

Requirements:
Knowledge and Experience
3+ years of experience as a Data Scientist, ML Engineer, or in a similar analytical role.
Strong programming skills in Python, with experience writing reusable libraries and working with data manipulation and ML libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow).
Solid grounding in statistics and machine learning: feature engineering, model selection, validation, and interpreting results for a business audience.
Hands-on experience with LLMs and Agentic AI: prompt engineering, retrieval-augmented generation (RAG), tool/function calling, and building or consuming agent frameworks.
Advanced proficiency in SQL and experience working with large-scale databases (e.g., PostgreSQL, MSSQL, Oracle).
Experience with AI/ML workflows, supporting model training, inference, and evaluation pipelines in production environments.
Genuine curiosity and a strong appetite to learn - eager to bring existing knowledge to the team and to grow it further.

Preferred Knowledge and Experience
Background in finance, trading systems, or financial market data.
Experience building or consuming MCP (Model Context Protocol) servers and clients.
Experience with workflow automation / orchestration platforms such as n8n, Airflow, or similar.
Experience with data visualisation and BI tooling for communicating analytical results.
Exposure to real-time data processing technologies (e.g., Kafka, Spark Streaming).

This position is open to all candidates.

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23/08/2026

Machine Learning Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Machine Learning Engineer to join the team that builds the predictive intelligence powering the Hello Heart app. You will own the ML models behind user engagement, cardiovascular risk stratification, and personalized health recommendations - the systems that determine what users see, when they're nudged, and how their health trajectories are shaped.

This role demands both statistical depth and engineering proficiency - you will be expected to take models from research through to deployment, write code built for production, and use AI coding assistants fluently as part of how you get work done.

Responsibilities
Lead end-to-end development of predictive ML models. From data exploration and feature engineering through training, validation, deployment, and ongoing monitoring across engagement and clinical risk domains.
Apply strong statistical foundations to model design, feature selection, uncertainty quantification, and interpretation of results
Write production-grade Python code that is clean, tested, and built for maintainability and scale.
Use AI coding assistants to accelerate development, code review, and documentation without sacrificing quality or rigor.
Partner with product managers, data engineers, and software engineers to translate strategic questions and user behavior patterns into measurable, data-driven solutions.
Research and implement cutting-edge ML techniques spanning supervised and unsupervised learning, causal inference, deep learning, and reinforcement learning to tackle complex healthcare challenges.
Contribute to MLOps infrastructure: model serving, versioning, evaluation pipelines, and monitoring.
Design and interpret A/B tests and other experimental methodologies to measure the impact of models, features, and interventions.

Requirements:
Qualifications
5+ years of hands-on experience developing, deploying, and maintaining ML models in production environments.
Bachelor's degree in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field - a strong statistical foundation is essential for this role.
Deep expertise in statistics and probability: distributions, inference, hypothesis testing, Bayesian methods, causal inference, and experimental design, with the ability to apply these rigorously in a healthcare context.
Strong software engineering skills in Python: production-grade practices, version control, testing, and reproducibility.
Proficiency using AI coding assistants as a core part of the development workflow.
Expertise with ML frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
Experience building or working within ML pipelines end-to-end, including feature engineering, model registries, and deployment tooling.
Strong ability to translate complex statistical and technical findings into clear insights and recommendations for both technical and non-technical stakeholders.

Advantage
Experience with cloud platforms (AWS preferred), containerization (Docker, Kubernetes), and MLOps platforms.
Prior work with healthcare or clinical datasets, including wearable device data, EMR, or claims data.
Experience with recommendation systems, reinforcement learning, or advanced causal inference.

This position is open to all candidates.

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19/08/2026

Backend Engineer - ML Platform

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for a Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

Requirements:
3+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
Strong proficiency in Python
Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
Fluent with AI-powered development tools like Cursor and Claude Code, and genuinely curious about what's next in GenAI, LLMs, and AI agents
Familiarity with AI concepts like RAG, embeddings, mixture-of-experts, prompt crafting, and LLM context engineering - an advantage
Sharp problem-solving instincts and the ability to move fast without cutting corners
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
Ready to work in an office environment most days of the week.

This position is open to all candidates.

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17/08/2026

Senior AI Engineer-AI Research

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Senior AI Engineer to join core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
The Responsibilities:
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

Requirements:
Must-have:
5+ years of experience in backend or AI engineering with strong coding skills (Python preferred).
Proven experience building and deploying production-grade AI/ML systems.
Strong software engineering fundamentals (data structures, algorithms, system design).
Experience with distributed systems, microservices, and cloud platforms (AWS/GCP/Azure).
Hands-on experience with LLMs and generative AI, including prompt engineering and model integration.
Experience with LLM frameworks and agent orchestration tools (e.g., LangChain, CrewAI, ADK, or similar).
Strong debugging and problem-solving skills, with an ownership mindset.
Nice-to-have:
Experience with ML frameworks such as PyTorch or TensorFlow.
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD for ML).
Background in NLP, LLM optimization, or agent-based systems in production.
Experience with large-scale data pipelines and NoSQL databases.
Experience with model evaluation, monitoring, and continuous improvement in production environments.
Contributions to open-source projects or research publications.

This position is open to all candidates.

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04/09/2026

Machine Learning Scientist II - GenAI Applications

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As a Machine Learning Scientist II, you will work within a cross-functional team of engineers and product managers to develop, evaluate, and deploy GenAI-powered solutions for scalable, customer-facing applications. Your work will focus on implementing agentic capabilities, contributing to evaluation frameworks, and delivering measurable business impact through data-driven experimentation.

Key Job Responsibilities and Duties:

Contribute to the design and development of end-to-end agentic systems, ensuring code quality and efficiency in production.

Build agentic solutions for different tasks and use cases using state-of-the-art techniques

Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges

Adhere to and promote established best practices in GenAI application development within the team.

Collaborate actively with team members, participating in code reviews, sharing knowledge, and contributing to a positive team environment.

Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.

Conduct deep data analysis to evaluate model performance, label quality, features exploration.

Work closely with ML engineers to ensure and improve the solutions latency/throughput meets product requirements and ensure deployment of your model to production.

Requirements:
Bachelors or masters degree in Computer Science, Engineering, Statistics, or a related field.

Minimum of 3 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.

Strong understanding and practical experience with Generative AI models, Natural Language Processing and engineering aspects of developing ML.

Experience executing research and development plans and contributing to large-scale ML applications.

Experience on multiple ML facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.

Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).

Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.

Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.

Excellent English communication and presentation skills, both written and verbal.

This position is open to all candidates.

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01/09/2026

Senior AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

Requirements:
Engineering Foundations:
- Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply.
- Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically.
- Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job.
- Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution.
- Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments.
- Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI.
- Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM).
AI / LLM Expertise:
- Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design.
Strong grasp of modern patterns for integrating LLMs into real workflows, including RAG, MCP (Model Context Protocol), vector databases, agents, tool use, and context engineering- with hands-on experience building with several of them.
- Production experience implementing LLM-powered systems end-to-end, using relevant tools and frameworks (e.g. LangChain, LlamaIndex, LangGraph, Haystack, Pydantic AI, vector stores like Pinecone/Weaviate/pgvector, observability tools like LangSmith or Langfuse).
- Solid foundation in core ML concepts; embeddings, evaluation, overfitting, generalization, and how classical ML relates to and differs from modern LLM-based approaches.
Nice to Have:
- Experience fine-tuning or distilling open-source models.
- Contributions to open-source AI/ML projects.
- Experience with streaming, real-time systems, or low-latency inference.
- Familiarity with prompt evaluation frameworks and LLM-as-judge methodologies.

This position is open to all candidates.

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25/08/2026

Senior Applied AI Scientist

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.

You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.

What Youll Do
Responsibilities:
Build, train, and ship detection models end-to-end, from raw data to production.
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities.
Own evaluation: design benchmarks, build labeled datasets, and define production standards.
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes.

Requirements:
5 years of hands-on ML and deep learning experience, with a track record of shipping, debugging, and diagnosing models in production.
Data-first mindset: you know how to define the right evaluation criteria for each model - before and after shipping, to ensure it delivers real quality and value in production.
Hands-on experience building and deploying agentic AI systems to production.
Proficiency in Python; experience with PyTorch, scikit-learn, HuggingFace, or equivalent.
Practical, applied mindset - focused on the problem, success metrics and impact, not lab research.
Background in security, trust & safety, or content moderation - an advantage.

This position is open to all candidates.

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06/08/2026

Principal/Senior ML Platform Engineer (Cortex)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

Requirements:
Core Engineering: 4+ years experience as a Senior ML Engineer, MLOps Engineer, or Backend Platform Engineer (Hands-On) working with cloud environments.
Model Lifecycle Engineering: Hands-on experience managing the technical lifecycle of diverse model architectures, spanning classic ML, LLMs/SLMs, and agentic/RAG systems. This includes engineering scalable data preparation and processing pipelines as well as implementing infrastructure for model training, fine-tuning, optimization, and high-throughput production serving.
Distributed Training & Compute: Strong foundational knowledge of Deep Learning concepts (neural network architectures, training dynamics, optimization techniques) paired with proven experience setting up and optimizing distributed training workloads across multiple GPUs (using PyTorch, DeepSpeed, Megatron-LM, or cloud-native training infrastructure).
Cloud & Infrastructure Architecture: Strong infrastructure knowledge within a major cloud provider ecosystem (GCP, AWS, or Azure), specifically leveraging managed AI platforms and services.
Python Expertise: Expert-level Python skills focused on ML infrastructure, pipelines, and automation frameworks.
CI/CD Integration: Experience with modern CI/CD patterns (such as GitLab CI or GitHub Actions) for automating software and model delivery loops.
AI Tooling & Development: Proficient in leveraging day-to-day AI tools and ecosystems (e.g., Claude, Gemini, MCPs, custom skills, and markdown formatting) to generate, review, and test code dynamically within your development cycle.
Preferred Qualifications
Strong GCP ecosystem experience.
Background in data science or deep learning workflows.
Cybersecurity domain knowledge.

This position is open to all candidates.

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02/09/2026

AI Team Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are hiring a hands-on AI expert to shape our intelligent platform, organizing complex real estate data into actionable insights and predictive models that power smarter investment decisions.

Responsibilities

AI/ML Architecture: Design and implement scalable AI systems using models such as
LLMs (e.g., OpenAI, Anthropic) and computer vision (e.g., YOLO, CLIP)
MCP Integration: Architect and orchestrate model context flows using MCP or similar
frameworks to deliver personalized, context-aware experiences
FinTech Platform Integration: Embed intelligent features into our backend and frontend
systems, ensuring seamless UX and robust performance
Hands-On Development: Write production-grade code across Python, TypeScript, and
Node.js. Own key modules and guide technical decisions
Team Leadership: Mentor a few developers, set engineering standards, and foster a
culture of experimentation and excellence
Data Strategy: Collaborate with product and data teams to define training datasets,
feedback loops, and model evaluation pipelines

Requirements:
6+ years of experience as a backend developer
2+ years developing AI/ML solutions
1+ years in a technical leadership role
Strong understanding of LLMs, prompt engineering, and model orchestration
Strong understanding of ETL pipelines, data preprocessing, and training workflows
Proficiency in Python, TypeScript (Bonus), Node.js (Bonus)
Proficient in Statistics, Fraud detection and Computer vision (Bonus) models
Experience integrating ML models into production systems with CI/CD pipelines
Solid grasp of FinTech data flows, security protocols, and compliance requirements
Excellent communication and mentoring skills
B.Sc. in Computer Science or related field (M.Sc. a plus)

This position is open to all candidates.

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8806929

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אירעה שגיאה בשליחת פרטיך למשרה

19/08/2026

AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are a fast-paced, technology-driven team where everyone's contribution impacts product success.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.

This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.

The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.

Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.

What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.

Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.

This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help our company move faster, automate smarter, and turn ideas into measurable business wins.

What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.

דרישות:
2-5 years of hands-on experience in AI Engineering, Data Engineering, Software Engineering, Data Science, Analytics Engineering, or a similar technical role.
Proven experience building and deploying AI-powered products, workflows, agents, automations, or business solutions in a real company environment.
Strong hands-on experience with LLMs, AI agents, prompt engineering, RAG, workflow automation, APIs, or AI development frameworks.
Ability to code and build practical solutions using Python, SQL, JavaScript/TypeScript, or similar languages.
Strong data experience, including ETLs, data pipelines, APIs, databases, data warehouses, and Snowflake.
Experience working in a SaaS or B2B technology company.
Strong business acumen, ownership, and communication skills, with the ability to work independently with stakeholders and drive projects from idea to production.
Degree in Engineering, Computer Science, Mathematics, Statistics, Physics, or a related quantitative field - advantage
Advantages
Experience with agent frameworks, RAG systems, vector databases, orchestration tools, Snowflake, Airflow, Rivery, Gitlab, Claude, OpenAI, or similar tools.
Experience working in a cybersecurity or data company.#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.

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8789170

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