דרושים » AI » Generative AI Engineer

Requirements:
Experience: 7+ years of proven experience designing, deploying, and managing production-grade Machine Learning and AI systems (with a strong foundation in data engineering and scalable pipelines).
Leadership: Demonstrated experience leading, managing, and mentoring data science or AI engineering teams.
Cloud & Infrastructure: Deep architectural expertise in the Amazon Web Services (AWS) ecosystem, with a track record of deploying large-scale solutions. Experience defining architectural standards to achieve milestones like the AWS ML Competency is a significant advantage.
Gen AI & Search: Extensive hands-on experience with Large Language Models (LLMs), deep learning frameworks, domain-specific prompting, and vector search/Elasticsearch.
Graph Technologies: Strong background in modeling complex data structures using Graph Databases (e.g., Neo4j) to build scalable pipelines for high-volume data.
Education: M.S. (or equivalent) in Engineering, Mathematics, Computer Science, or a related quantitative field.
Communication: Excellent interpersonal skills with the ability to lead customer-facing engagements and translate complex technical concepts into business value.
Fluent in Hebrew and English

Requirements:
Technical Expertise:
Programming: Advanced proficiency in Python for backend development and AI applications
GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.)
Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures
Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques
Cloud Platforms:
Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS)
Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.)
Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services
Software Engineering: Strong background in microservices architecture, API development, and production system design
AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques
Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration
OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing
Data Pipelines (Advantage): Experience building and maintaining data processing pipelines
Professional Experience:
Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience
Production Systems: Proven track record of deploying and maintaining AI solutions in production environments
Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions
Education & Background:
Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field
Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio)
Soft Skills:
Problem-Solving: Excellent analytical and creative problem-solving abilities
Communication: Strong technical communication skills for both technical and non-technical audiences
Collaboration: Proven ability to work effectively in cross-functional teams
Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies
Consulting Mindset: Ability to understand client needs and provide strategic technical guidance

Requirements:
5+ years of backend engineering experience building and operating production systems at scale, with a strong sense of ownership from design through deployment and operations.
Deep expertise in microservices architecture, API design, and distributed systems, with cloud-native design experience on AWS (or GCP/Azure) using Kubernetes and Helm.
Proficiency in Python for building scalable backend services, with a focus on clean, production-grade code and seamless integration of AI components.
Hands-on experience integrating Generative AI into backend systems, including LLMs, knowledge bases, and agent frameworks, plus familiarity with tooling such as AWS Bedrock, LangChain/LangGraph and vector databases.
Solid experience with data and messaging technologies - SQL/NoSQL databases, caching layers, and message brokers such as PostgreSQL, Redis, Kafka, RabbitMQ, and Elasticsearch.
Strong command of observability practices, with hands-on experience in tools such as Prometheus, Grafana, or Splunk for monitoring, distributed tracing, and alerting.
Fluency in agile development and delivery tooling such as Jira, with a track record of consistently shipping high-quality software in fast-moving environments.

Requirements:
Bachelors or Masters degree in Computer Science, AI, Engineering, or a related field; Ph.D. is an advantage.
8+ years of software engineering and AI experience, with hands-on expertise in LLMs, Generative AI, and Agentic AI.
Recognized expertise and leadership in Agentic AI, with significant contributions to Agent platforms, frameworks, or enterprise AI solutions.
Ability to combine technical vision with hands-on execution, from architecture and prototyping to production.
Proven experience architecting, building, and scaling production-grade Agentic AI platforms and systems.
Deep expertise in reasoning and planning, memory, RAG, tool use, context engineering, multi-agent systems, evaluation, and observability.
Strong expertise in Python, software architecture, distributed systems, cloud, APIs, and AI infrastructure.
Strong technical leadership, presentation, and communication skills, with the ability to influence technology direction and represent openJiuwen globally.
Advantages:
Strong understanding of enterprise AI architecture, including reliability, security, scalability, performance, and cost efficiency.
Experience with leading Agentic AI platforms, frameworks, and ecosystems, such as OpenAI Agents SDK, Claude ecosystem, OpenClaw, Hermes, or equivalent technologies.
Experience leading or contributing to global open-source and developer communities.
Demonstrated industry influence through conferences, publications, developer communities, enterprise engagements, research papers, patents, or advisory roles.
Experience with Physical AI and embodied agent systems.

Requirements:
Requirements
5+ years of backend software engineering experience.
Strong Python development skills, preferably with FastAPI and/or Django.
Experience designing scalable distributed systems and microservice architectures.
Experience building AI-powered applications or integrating LLMs (AWS Bedrock preferred).
Experience working with SQL and NoSQL databases, ORM frameworks, and query optimization.
Familiarity with event-driven architectures, messaging technologies (Kafka, Celery, or similar), and distributed caching (Redis).
Experience building REST, GraphQL, or gRPC APIs using Nest.JS or FastAPI or Django and LiteStar.
Experience with Docker, CI/CD pipelines, Infrastructure as Code (IaC), and cloud-native development.
Knowledge of monitoring and observability tools such as OpenTelemetry, Prometheus, Grafana, Datadog, or similar

Requirements:
what we need to see:
b.sc. in Computer Science, software engineering, or a related field, or equivalent experience.
3+ years of software development experience.
strong Python skills. you build well-structured systems, not just scripts.
hands-on experience building applications with llms, such as agents, tool use, or rag.
strong problem-solving skills and the ability to take a feature from idea to production.
excellent verbal and written english. we are a multi-language team that works across sites and time zones.
ways to stand out from the crowd:
experience evaluating the quality of llm-based systems.
knowledge of the Linux Kernel, networking, or device drivers.
experience with TEST automation or verification.
Full Stack or DevOps experience.
a track record of ai tools that real users adopted.
we are committed to fostering a diverse work environment and proud to be an equal opportunity employer. as we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements:
4+ years of experience in software development, data, analytics, AI, or related technology domains.
Hands-on experience with Python, APIs, data platforms, cloud technologies, and AI tooling.
Strong understanding of AI, GenAI, LLMs, automation, and modern technology architectures - including how LLM solutions are actually built and evaluated (RAG, prompting, agents, guardrails).
Practical grasp of AI delivery methodology: standards, governance, and the operational practices that keep AI solutions reliable in production.
Ability to translate business needs into technical requirements and actionable implementation plans.
Experience working with cross-functional development and technology teams.
Strong facilitation, training, and stakeholder management skills.
Ability to produce clear solution/reference architecture and technical documentation.
Excellent communication and presentation abilities.
Self-driven, proactive, and engaged with AI and emerging technologies.

Requirements:
Experience: 7+ years in Data Engineering, BI, Data Science, or Technical Leadership, Managerial Experience: with 3+ years managing technical teams. Technical Depth: Proven hands-on experience with modern cloud data platforms (Snowflake, BigQuery, Databricks, or AWS Services) and ETL/ELT pipelines. Applied AI / GenAI: Practical experience deploying production ML models, LLMs, RAG systems, or AI agents. Systems Integration: Track record of integrating enterprise ecosystems (ERP, CRM) with large-scale telemetry and logs. Governance & Security: Familiarity with security, privacy, and compliance standards (SOC 2, GDPR). Communication & Leadership: Strong ability to influence cross-functional stakeholders and translate complex technical topics into business strategy. Education: B.Sc./M.Sc. in Computer Science, Information Systems, Engineering, or a related field.

Requirements:
3+ years of hands-on experience in DevOps, automation, systems engineering or software development.
Strong scripting/programming skills.
Hands-on experience with LLMs / GenAI: prompt engineering, RAG, agents, function/tool calling.
Experience with REST APIs, JSON, webhooks and integrating SaaS/enterprise systems.
Working knowledge of Docker / Kubernetes, CI/CD and Git.
Strong communication skills; able to work with non-technical stakeholders and explain AI clearly.
Fluent Hebrew and English.
Nice to have:
Experience with MCP (Model Context Protocol) servers/clients.
Familiarity with identity & access (Entra ID/AD, OAuth, SSO) and security best practices.
Experience with AI platforms such as Amazon Quick / Bedrock, Azure OpenAI, Copilot Studio, Open WebUI, or LangChain/LangGraph.

Requirements:
:Key Responsibilities Information Systems Management Own and manage the company's internal business systems, SaaS platforms, and operational tools. Lead the implementation, configuration, integration, and continuous improvement of business applications. Ensure system reliability, user access management, data integrity, and operational excellence. Partner with internal stakeholders and external vendors to align systems with evolving business needs. Identify opportunities to simplify technology stacks, enhance data quality, and improve system efficiency. AI & Business Process Automation Drive the organization's AI and automation strategy by identifying high-impact opportunities across business functions. Design, build, and maintain automated workflows using platforms such as n8n, Make, Zapier, or similar tools. Implement AI-powered solutions using leading LLM technologies including OpenAI, Claude, and related AI platforms. Develop intelligent agents, assistants, and workflow automations to support business operations. Integrate business systems through APIs, webhooks, and automation frameworks. Automate repetitive and manual processes across departments including Operations, Finance, HR, Customer Success, and Sales. Monitor, measure, and optimize automation initiatives based on efficiency gains, cost savings, quality improvements, and business impact. Systems Integration & data Management Build and maintain integrations across internal and external platforms using APIs and modern integration technologies. Work with structured and unstructured data to support automation and AI-driven initiatives. Ensure proper governance, security, privacy, and compliance standards are maintained across systems and AI implementations. Troubleshoot and continuously improve system integrations and workflow reliability. Maintain clear documentation of system architecture, integrations, and automation processes. Business Partnership & Project Leadership Collaborate directly with business leaders to understand challenges, define requirements, and identify improvement opportunities. Translate business needs into scalable technical solutions. Lead technology and automation projects end-to-end, from discovery and design through implementation, testing, deployment, and support. Help drive AI adoption across the organization by enabling teams and promoting best practices. Remain up to date with emerging technologies, AI capabilities, automation tools, and industry trends.