לוח משרות דרושים הייטק AI עבודה היברידית

Requirements:
Drive technical excellence through your profound knowledge of python across diverse projects.
Implement systems with frontend and AI backend, including RAG systems
Harness your CUDA expertise to maximize the performance and efficiency of our computing platforms.
Oversee projects from ideation to completion, ensuring quality, timeliness, and budget adherence.
Mentor team members and foster a growth-oriented learning environment.
Apply your critical and creative problem-solving skills to troubleshoot and resolve intricate technical issues.
Working with Artificial Intelligence algorithms using Neural Networks
Requirements:
8+ years of hands-on experience in python or c++ showcasing a deep understanding of the languages, its intricacies, and best practices.
Bachelors or Masters degree in Computer Science,
Experience as a Team Leader/ Technical Leader - must
Proven experience in leading and managing complex technical projects, demonstrating strong project management skills.
Exceptional problem-solving skills with a proven ability to troubleshoot complex issues, showcasing strong analytical and critical thinking abilities.
Outstanding communication skills, with the ability to explain complex concepts in a clear and concise manner to both technical and non-technical stakeholders.
Excellent leadership capabilities, with a track record of mentoring and guiding team members to foster professional growth and development.
Experience working with AI, GenAI
Experience with GPU, CUDA - optional

Requirements:
Minimum of 5 years of experience as a Back End developer.
Deep knowledge of Generative AI principles, including Large Language Models (LLMs) and RAG techniques and, modern deployment architectures.
Ability to lead team to design services, modules, APIs, and folder structures that enable REST API communication and facilitate a plug-and-play approach for various agent pods (compatible with langgraph, pydanticAI, etc.)
Practical Implementation: Hands-on experience in implementing and integrating new ideas and tools within the GenAI landscape.
Programming and Tools: Proficiency with Python, PySpark, Langchain, LlamaIndex, RAG, ChromaDB, QDrant, Weaviate, Neo4j, Knowledge Graphs, AWS Bedrock, GCP Vertex, Azure OpenAI, Git/GitHub, Docker, SQL, FastAPI, PyTorch/TensorFlow, and Pydantic.
Cloud Platforms: Experience with managed cloud services provided by hyperscalers such as AWS, Azure, or GCP.
Excellent problem-solving and analytical skills. Degree in Computer Science, Artificial Intelligence, Machine Learning or a related field.
Advanced level of English.
Working Israeli permit- a must
B.A/M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc- an advantage

Requirements:
At least 4 years of experience in software development, with a focus on building scalable and maintainable systems.
Proven experience building agentic AI solutions, including:
Designing and implementing RAG pipelines.
Developing prompt-engineering strategies for security-critical applications.
Constructing evaluation frameworks to measure model performance in production.
Integrating LLMs into live environments to drive autonomous workflows.
Strong communication skills and the ability to work effectively within a collaborative team environment.

Requirements:
- 3-6 years of experience in software development, with a strong foundation in backend or full-stack development.
- Proficiency in integrating AI technologies, such as LLMs, into software solutions.
- Experience developing scalable, cloud-based distributed systems in microservices architecture.
- Familiarity with version control systems, especially Git, and collaborative development workflows.
- Strong understanding of secure coding practices and principles.
- Excellent communication skills, fast learner, results-driven, and a strong team player.
Desired qualifications:
- Hands-on experience with tools like GitHub Copilot, Claude, or Cursor.
- Experience with AWS services like S3, Lambda, and Bedrock.
- Experience working with Cloud Native designs and ecosystem (Docker, Kubernetes, Helm).
- Background in cybersecurity or a strong understanding of security best practices.
- Experience with big data technologies and processing large datasets.