לוח משרות דרושים הייטק AI משרה מלאה

Requirements:
Strong proficiency in Python for backend development and AI-related systems
Solid understanding of large language models and generative AI techniques
Experience contributing to agent-based workflows or orchestration logic
Practical experience with prompt design and prompt optimization techniques
Understanding of microservices architecture and API-based system design
Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience:
Up to 2 years of experience in software engineering, AI, or ML-related roles
Experience contributing to production or production-adjacent systems
Exposure to client-facing or consulting-style project delivery is an advantage
Education & Background:
Bachelors degree in Computer Science, AI, Machine Learning, or related technical field
(or equivalent practical experience and portfolio)
Soft Skills:
Strong analytical and problem-solving abilities
Clear technical communication skills
Ability to collaborate effectively across teams
Adaptability and eagerness to learn in fast-paced environments
Consulting mindset and client-oriented approach

Requirements:
Bachelors degree (B.Sc) in Computer Science, Engineering, Information Systems, Data Science, or a related field.
3+ years of experience in project or product management, with hands-on involvement in data, AI, or technology-driven initiatives.
Strong understanding of data architectures, data pipelines, analytics frameworks, and AI-driven systems.
Proven experience delivering AI or Generative AI solutions into production environments.
Ability to translate complex technical concepts into clear, structured communication for non-technical stakeholders.
Experience managing complex, multi-stakeholder projects with strong organizational and execution skills.
Analytical mindset with the ability to make data-driven decisions and assess trade-offs.
Excellent verbal and written communication skills in English.
High level of ownership, independence, and ability to perform in dynamic, fast-paced environments.
Nice to Have:
Background in AI, machine learning, or advanced analytics projects.
Experience working in consulting or client-facing delivery roles.
Familiarity with cloud platforms and modern AI tooling.

Requirements:
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:
Technical Expertise:
Advanced proficiency in Python for backend development and AI systems
Deep understanding of large language models and generative AI techniques
Hands-on experience designing and implementing multi-agent architectures
Advanced prompt engineering and orchestration strategies
Strong background in microservices architecture, API development, and production system design
Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience
3-4+ years of experience in AI/ML development with significant GenAI project exposure
Proven experience in end-to-end software development in Python
Proven experience deploying and maintaining AI systems in production
Client-facing experience in technical consulting or solution delivery roles
Advantages:
Hands-on experience developing directly against LLM provider SDKs and APIs (e.g., OpenAI, Anthropic, Google), including tool/function calling, streaming, and advanced orchestration patterns
Docker and Kubernetes experience
OCR systems and document intelligence experience
Data pipeline development and maintenance experience
Education & Background:
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related field (or equivalent demonstrated industry experience)
Soft Skills:
Strong problem-solving and analytical capabilities
Excellent technical communication skills
Ability to collaborate effectively across teams
Adaptability in fast-paced, evolving technical environments
Consulting mindset with strong client focus

Requirements:
5+ years of experience in AI/ML engineering, performance optimization, or ML systems.
Deep understanding of LLM architectures, training & inference mechanics, and modern ML frameworks.
Strong proficiency in PyTorch ecosystem, with a specific focus on performance tuning via Triton, Cuda or MLIR-based compiler frameworks.
Hands-on expertise profiling and optimizing kernels (GEMM, attention, softmax, token pipelines).
Demonstrated experience running or tuning MLPerf or similar large-scale benchmarks.
Strong Python and C++ development skills.
Proven leadership experience: mentoring, guiding, or managing engineers.

Requirements:
Must-Have
5-8 years of software engineering experience, with at least 2-3 years focused on AI/ML engineering
Hands-on experience building production-grade LLM applications - RAG, agents, tool use, or fine-tuning
Proven experience designing and running multi-agent systems in production: orchestration patterns, agent state management, retries, and graceful degradation
Experience monitoring and observing AI agents in production - execution tracing, latency tracking, failure detection, and alerting (e.g., LangSmith, Arize, custom observability stacks)
Proficiency with agentic frameworks: LangChain, LangGraph, and/or AWS Bedrock AgentCore
Strong Python skills and comfort working across the full AI application stack
Experience designing and operating MLOps pipelines (model versioning, deployment, monitoring)
Solid understanding of transformer-based models, embeddings, and vector databases (e.g., Pinecone, Weaviate, pgvector)
Comfortable working in cloud environments (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes)
Strong problem-solving skills and ability to work autonomously in a fast-paced environment
Nice-to-Have
Background in cybersecurity - threat detection, SIEM, SOC automation, or security data analysis - a significant plus for this role
Familiarity with networking concepts (SDN, cloud-native networking, BGP, telemetry)
Experience with model evaluation and benchmarking (LLM-as-judge, RAGAS, or custom eval harnesses)
Exposure to MCP (Model Context Protocol) for tool-augmented agentic workflows
Prior experience in enterprise SaaS, networking, or telecom domains
Publications, open-source contributions, or projects in the LLM/GenAI or agentic AI space
Our Stack
Python PyTorch OpenAI / Anthropic APIs LangChain LangGraph AWS Bedrock AgentCore LangSmith Kubernetes Kafka Elasticsearch AWS PostgreSQL GitHub Jira Confluence.

Requirements:
5+ years in Product Operations, R&D Ops, or related role at a scaling B2B SaaS company.
Deep Jira expertise - can self-serve on configuration, workflows, automations, and reporting.
Proven track record designing processes that measurably improve team velocity and output.
Strong analytical skills - turns data into dashboards and dashboards into decisions.
Excellent cross-functional communicator - translates between Engineering, Design, Sales, CS, and Marketing with ease.
Passionate about automations, AI, and efficiency - defaults to building systems, not fighting fires.
Experience with product tool stacks (Jira, Notion, PostHog, or similar).
Property management, PropTech, or vertical SaaS experience is a plus.

Requirements:
5+ years in Security Engineering/AppSec/Cloud Security (or similar), including 1-2+ years securing AI/ML or data‑intensive systems (GenAI preferred).
Hands‑on experience with AWS and/or Azure and modern app stacks (Python/TypeScript, REST/gRPC, containers/Kubernetes, IaC such as Terraform).
Practical understanding of LLM attack surfaces (prompt injection, data leakage via tools, training/fine‑tune poisoning, model supply chain) and mitigation patterns.
Familiarity with identity and access for AI workloads (OAuth2/OIDC, service principals, role tokens, PIM), and secure secret management/KMS.
Experience implementing observability/telemetry and routing findings to SIEM; comfort balancing privacy with traceability.
Ability to translate controls into developer-friendly libraries, docs, and CI/CD checks; strong written communication in English and Hebrew.
Comfort working in a regulated environment and mapping controls to frameworks (FFIEC, SOC 2, PCI DSS).
Nice to have:
Financial services background or other high‑assurance domains.
Exposure to Duende IdentityServer, SSO/SCIM, and enterprise authorization patterns.
Experience with vector databases (e.g., OpenSearch, pgvector, Pinecone) and secure RAG architectures.
Familiarity with guardrail tooling (e.g., Azure AI Safety features, Amazon Bedrock Guardrails) and policy engines (OPA/Rego).
Prior work in AI red‑teaming or safety evaluation harnesses; contributions to OSS or published talks.

Requirements:
Demonstrated AI fluency - you have real experience building with tools like Claude Code, OpenClaw, Cursor, Replit, or similar.
Youve built AI-assisted projects: agents, automations, apps, content systems or workflows.
Passion for marketing and an intuition for what makes people click, sign up, and stick around - formal marketing experience is a plus, not a requirement
High agency and independence - you own projects from A to Z with minimal hand-holding
Strong written communication - you can simplify complex ideas and write copy that connects
Comfort with speed and ambiguity - you thrive in fast-moving environments where priorities shift and you need to figure things out as you go.

Requirements:
A Product Manager with 4+ years of experience building data-driven, consumer-facing products ideally with experience in platforms, AI-driven systems, or complex user workflows.
Youre passionate about shaping product experiences in the age of AI. You think deeply about how automation and control coexist, and you know how to translate ambiguous opportunities into structured, scalable solutions.
You are:
Highly analytical and comfortable working with data, experimentation, and user research
Experienced in defining end-to-end product strategies and measurable KPIs
Strong in user experience thinking, with the ability to design complex workflows
Technically savvy, able to work closely with engineers on scalable infrastructures and AI-powered capabilities
Curious, innovative, and not afraid to challenge assumptions
Cross-organizational leadership and experience working with AI-powered products are strong advantages.

Requirements:
5+ years of experience in data science, with experience in managing full-cycle projects from initial concept to production deployment
Msc / PhD in Computer Science, Mathematics, Physics, Statistics, or a related field
Comprehensive understanding of machine learning and deep learning principles and techniques, including hands-on experience
Experience in leading a data science / research team.
Specialized expertise in LLMs, Transformers architectures and computer vision (multimodality is an advantage)
Ability to write production-ready code
Publications and talks at leading conferences - an advantage.

Requirements:
Strong programming skills, preferably in Python.
Exceptional analytical skills and a passion for solving complex problems.
Thorough understanding of how AI works and familiarity with language models.
Understanding of vector databases and other relevant data structures.
Working knowledge in various databases and messaging technologies is a strong plus. (SQL, Redis, Kafka etc.)
Excellent communication skills in English.
Mature, thoughtful attitude with the ability to operate in a collaborative, team-oriented culture.
A strong delivery mind-set, drive to get things done.
Experience in finance is not required.

Requirements:
all you need is:
m.sc. in Computer Science, electrical engineering, or a related field (ph.d. - advantage).
3+ years of hands-on industry experience in deep learning, with a strong background in designing and training neural networks.
experience with reinforcement learning (academic coursework, research, or practical application) - strong advantage.
strong programming skills in Python.
experience with C ++ and/or cuda or other performance-oriented programming - advantage.
proven ability to tackle complex, open-ended problems and work effectively in iterative, research-driven environments. we change the way we drive, from preventing accidents to semi and fully autonomous vehicles. if you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Requirements:
all you need is:
m.sc/ph.d. in Computer Science, electrical engineering, robotics, Machine Learning, applied mathematics, or a related field.
proven experience in Machine Learning and deep learning.
demonstrated ability to conduct independent research (publications in top-tier venues such as neurips, icml, iclr, cvpr, corl, etc. - advantage).
strong programming skills in Python ; solid C ++ experience - advantage.
experience in training large-scale models and working with real-world data.
intellectual curiosity, scientific ownership, and comfort operating in open-ended research environments.
We change the way we drive, from preventing accidents to semi and fully autonomous vehicles. if you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Requirements:
what we need to see:
bachelors, masters or higher degree in computer engineering, Computer Science, applied mathematics or related computing focused degree (or equivalent experience).
5+ years of relevant software development experience.
excellent Python programming skills, software design, and software engineering skills
awareness of the latest developments in llm architectures and llm inference techniques
experience working with deep learning frameworks like pytorch and huggingface
proactive and able to work without supervision
excellent written and oral communication skills in english
ways to stand out from the crowd:
prior experience with a llm inference framework (tensorrt-llm, sglang, vllm, etc.) or a DL compiler in inference, deployment, algorithms, or implementation
prior experience with performance modeling, profiling, debug, and code optimization of a DL /hpc/high-performance application
excellent C / C ++ programming and software design skills, including debugging, performance analysis, and TEST design.
architectural knowledge of cpu and gpu
gpu programming experience (cuda or opencl)