דרושים » הנדסה » Senior AI Engineer

Requirements:
2-4 years of experience as a Business Applications/Web Developer, IT/System Engineer, Automation Engineer, or AI-focused Solution Engineer, or equivalent hands-on project experience.
Practical experience working with LLMs, AI agents, and RAG-based solutions, and connecting them to real-world business workflows.
Strong experience with APIs, webhooks, and system integrations.
Hands-on experience with JavaScript for building and extending applications or integrations (Python is a plus).
Experience working with low-code/no-code automation tools such as n8n, Workato, Make, or similar platforms.
Curiosity and motivation to create AI-driven helpers and automation experiences that streamline how employees work and interact with internal systems.
Strong problem-solving and self-learning abilities, with a hands-on approach to tackling complex challenges and delivering real solutions.
Strong communication skills, with the ability to clearly convey technical ideas and solutions to a wide range of audiences.

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:
Overall of 5 years of hands-on experience (3 years automation, 2 years in GenAI)
Hands-on experience building AI-powered workflows or agents
Strong understanding of LLMs and prompt engineering
Experience with API-based integrations and SaaS systems
Familiarity with automation platforms and orchestration tools
Experience with agentic patterns (planner-executor, tool-using agents, multi-agent setups)
Experience implementing human-in-the-loop and fallback mechanisms
Understanding of AI limitations, bias, and reliability concerns
Strong problem-solving and systems-thinking mindset
Ability to work independently and drive initiatives end-to-end
Excellent communication with both technical and non-technical stakeholders.

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
2-3+ years of experience in AI/ML development with significant GenAI project exposure 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
Bachelors or Masters 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:
Extensive hands-on experience in Business Applications and/or software development
Experience building end-to-end AI solutions and automations
Deep understanding of business processes and a drive to impact business results
Experience with AI platforms (e.g., OpenAI, Claude, Gemini) and automation/orchestration tools (e.g., n8n, Make.com, LangChain)
Development capabilities, preferably in Python
Hands-on experience designing and consuming REST APIs, working with HTTP methods, authentication mechanisms, and integrating GTM platforms into AI-driven workflows.
High degree of independence and initiative - able to run projects autonomously
Sharp analytical skills and a structured problem-solving mindset
Excellent written and verbal communication skills; able to bridge technical and non-technical stakeholders
Passion for continuous learning, experimentation, and staying current with AI trends
Experience working with GTM or RevOps teams in a SAAS company - a big advantage
Experience with Salesforce - a big advantage.

Requirements:
3+ years of experience as a Salesforce Administrator, or equivalent extensive hands-on experience working with Salesforce - must
2+ years of proven experience in internal tooling, automation engineering, or system integration roles - must.
Hands-on programming experience with Python or JavaScript, including working with APIs, building backend logic, and optimizing data flows.
n8n development - Strong advantage.
Proven experience working with AI-driven automation and enrichment (LLM-based workflows), including prompt engineering and applying AI tools to internal systems (i.e. n8n).
Strong proficiency in SQL, preferably PostgreSQL, with experience designing efficient data models and ETL/ELT processes.
Experience building or maintaining internal applications and dashboards using platforms such as Power BI, Tableau, or equivalent internal tools frameworks.
Excellent problem-solving and analytical skills, with the ability to translate complex operational and analytical needs into scalable technical solutions.
Strong communication skills and the ability to work collaboratively with both technical and non-technical stakeholders.
High level of English.

Requirements:
B.Sc. in Computer Science, Engineering, Data Science, or a related quantitative field.
3+ years of experience in AI/ML engineering, solutions engineering/architecture, or related technical roles.
Hands-on experience with modern AI/ML workflows, including large language models (LLMs), MLOps, or production-grade model deployment.
Proven track record of engaging with enterprise customers, including pre-sales activities (demos, PoCs, workshops).
Strong software engineering and/or data engineering fundamentals (e.g., APIs, cloud services, data pipelines).
Ability to work independently while managing multiple client-facing projects.
Excellent communication skills, with the ability to explain complex AI concepts to both technical and business stakeholders.
Customer-first mindset, with a focus on delivering practical, value-driven AI solutions.

Requirements:
What youll need:
Excellent coding skills in Python/TypeScript, with at least 5 years of hands-on experience building reliable backend services, agents and tooling. Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) is a strong advantage.
Experience designing, deploying, and maintaining production systems that integrate ML components, including APIs, microservices, model serving layers, feature pipelines, monitoring, and CI/CD/MLOps workflows.
Solid experience with AI related contexts Understanding of prompt engineering and LLM optimization techniques, RAG architecture
Solid understanding of distributed systems concepts, performance optimization, observability, and operating services at scale.
Strong communication skills, with the ability to bridge technical, product, and business perspectives.
Prior experience in cybersecurity, fraud prevention, or identity management is a plus, especially with secure system architectures or ML-augmented decisioning systems.
Advantages:
Experience integrating with LLM APIs (OpenAI, Anthropic Claude, etc.)
Experience with agent frameworks (LangChain, LlamaIndex, AutoGPT)
Background in ML/AI concepts and model deployment
Experience with message queues (RabbitMQ, Kafka) and event-driven architectures
Experience with function calling and tool use patterns in LLMs.

Requirements:
5+ years of professional backend engineering experience.
Strong proficiency in at least one backend programming language (Java etc).
Experience building and maintaining production-grade APIs and microservices.
Solid understanding of distributed systems, data structures, and algorithms.
Experience with SQL and NoSQL databases.
Track record of delivering consumer-facing products at scale.
Experience with AI/ML platforms and services (OpenAI, Hugging Face, etc.)
Familiarity with LLMs, RAG, or conversational AI.
Knowledge of vector databases and embedding technologies.
Experience with cloud platforms (AWS, GCP, Azure).
Understanding of AI/ML concepts and implementation patterns.

Requirements:
At least 3 years experience in Python / TS working with AI/ML frameworks
At least 5 years of backend experience with at least one additional programming language (Java / C# / Node.js / C++)
At least 3 years experience working with database solutions (RDBMS, NoSQL, Vector)
Proven experience with writing efficient and useful LLM prompts
Proven experience building LLM-based solutions and integrating them into products
Strong system and architecture design skills, particularly in designing LLM based systems
Experience or at least substantial knowledge of GenAI technologies such as agentic flows, RAG, model fine-tuning / distilling, prompt engineering, context engineering
Hands-on experience with cloud platforms and their AI/LLM services
Experience working on a SaaS product - Advantage
Experience working with customers and direct customers feedback - Advantage
Experience using observability / profiling / remote debugging tools - Advantage
Passionate about AI and up to date with industry trends - Advantage