לוח משרות דרושים הייטק AI

Requirements:
5+ years of experience as a Product Manager in a B2B SaaS environment, preferably with technical products, thriving in a fast-paced startup environment.
Proven experience building and launching AI-powered products, including conversational and chat-based experiences, from discovery through delivery, adoption, and iteration.
Strong technical foundation with an understanding of software development processes, cloud environments, and modern SaaS architectures.
Proven track record of leading cross-functional squads in Agile environments, successfully driving products from concept to launch and adoption.
Highly data-driven mindset, with experience defining success metrics, using product analytics, and making decisions based on measurable outcomes and customer impact.
Experience working with experimentation and evaluation approaches to measure AI quality and improve performance over time.
UX-focused product approach, collaborating with design to simplify complex technical challenges into intuitive solutions.
Excellent communication and stakeholder management skills, with the ability to influence without direct authority.
Fluent in English, both written and spoken.
Bachelors degree in Computer Science, Engineering, or a related field (preferred).

Requirements:
AI & Optimization: Leverage AI-based tools to generate, refactor, and optimize integration logic.
Technical Core: Understanding of REST APIs and experience with integrating systems and syncing data. Use tools like Postman/other dev tools for testing, troubleshooting and POCs.
Security & Cloud: Familiarity with OAuth, SSO, and enterprise environments (Azure/AWS/Active Directory).
Communication Pro: Exceptional English (written/spoken) with the ability to explain complex technical concepts to non-technical stakeholders.
Consultative Mindset: A mix of analytical problem-solving and the "people skills" needed to thrive in customer-facing scenarios.
This role is part-time 0.5 FTE (20 hours a week)

Requirements:
4 years in Data Science, with industry experience in building and optimize AI/ML models
Specialized expertise in modern machine learning methods related to Natural Languages Processing (Transformers, Embeddings, LLMs)
Experience deploying AI/ML services and applications on at least one major cloud platform (Azure, AWS, GCP)
Pratrical skills using modern ML and Generative AI frameworks (Langchain, PyTorch, Tensorflow, Hugging Face and other open-source/ APIs and similar)
Experience with LLM applications and techniques, such as Retrieval-Augmented-Generation (RAG), Chane-of-Thought (CoT) prompting, and open-source LLMs fine tuning
Ability to write production ready code, with strong expertise in designing and implementing ML pipelines
Excellent problem-solving skills with a critical and creative mindset
Exceptional communication skills and a collaborative approach to teamwork
BSc, master or PhD in appropiate technology field (Computer Science, Electrical Engineering, Statistics, Applied Math, etc.)
A Big Plus If You Have::
Extensive experience in integrating and working with vector databases (e.g. Elastic, Milvus and more) for high-performance similarity search, semantic search and embeddings management.
Experience with building continuous integration and monitoring for Machine Learning applications.

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:
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)

Requirements:
what we need to see:
b.sc. (or equivalent experience) in Computer Science, ai, Machine Learning or related field
4+ years of experience in a managerial role.
3+ years of experience implementing production ai/ml systems
8+ overall years of experience in software development
strong understanding of modern Machine Learning domains, known algorithms, architectures and techniques
proficiency in Python
capable of multi-tasking, ability to drive both people and tasks.
effective communication and collaboration skills
demonstrated leadership with the ability to inspire and motivate team members.
ways to stand out from the crowd:
track record of delivering high-quality work on time and meeting project timeline.

Requirements:
what we need to see:
7+ years in applied ml/ai or large-scale systems, with 3+ years crafting agentic or llm-powered applications in production environments.
b.sc in Computer Science / electrical engineering
proven ownership of at least one end-to-end agentic system or llm application: requirements, architecture, implementation, evaluation, and incremental hardening in production.
strong software engineering skills in Python and one systems language ( C ++ or rust preferred); experience integrating with gpus, cuda, or performance-critical services.
proficient in pytorch or tensorflow; skilled in tool use, rag pipelines, and model adaptation.

Requirements:
what we need to see:
hold a m.sc. or ph.d. in Computer Science, electrical or computer engineering from a leading university (or equivalent experience).
5+ years of industry experience (or equivalent) in ai pipelines architecture or related fields.
industry experience building and shipping ai-powered tools or ml pipelines (not just training models - end-to-end delivery).
strong understanding of llm capabilities and limitations - prompt engineering, fine-tuning, rag, agent architectures.
experience with at least two of: reinforcement learning, classical ml, NLP /information retrieval, evaluation framework design.
can reason about trade-offs: when to use which approach, with real reasoning backed by shipping experience.
strong programming skills ( Python required; familiarity with ml frameworks - pytorch, huggingface, etc.).
ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
ways to stand out from the crowd:
experience with llm-based code generation, code review, or Developer tooling.
familiarity with eval frameworks and feedback loop design (online and offline evaluation).
experience with ai agent orchestration (multi-agent systems, tool use, planning).
shown research track record (publications, open-source contributions).
knowledge of ai-assisted development tools and their underlying architectures.