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Location: Holon
Job Type: Full Time
DealHub.AI is building the future of agentic revenue technology. Trusted by leading global businesses, we’re redefining what revenue teams can achieve with AI and agentic execution across the deal lifecycle. Our mission is simple: help businesses Own Your Revenue with greater speed, intelligence, and governance. As an Solution Expert you will serve as the technical trusted advisor for our customers, bridging AI capabilities with their specific business goals and revenue workflows You will embed deeply with customers. Part consultant, part engineer, part strategic advisor: leading AI sessions, configuring AI-driven workflows using DealHub MCP, training users on best practices, and ensuring measurable business outcomes. You'll collaborate closely with Customer Success, Product, Support, and Engineering teams, and will be the go-to expert for any AI-related technical solution. This is an ideal role for someone who thrives at the intersection of cutting-edge AI technology and real-world business challenges. This role is ideal for someone who thrives on ambiguity, moves fast, and finds equal satisfaction in writing clean code and presenting a solution to a CFO. Key Responsibilities
* Embed deeply with customers to understand their technical environment, business processes, and AI workflows and then design and build solutions that fit.
* Build and deploy AI-powered workflows, MCP-based automations, and intelligent features within the DealHub platform tailored to each customer's use case taking into account the integration landscape such as Salesforce, HubSpot, Dynamics, NetSuite, and billing platforms.
* Leverage LLM, AI, APIs, webhooks, data pipelines, automation scripts.
* Lead technical AI sessions — review requirements, demo solutions, help build agents and perform training.
* Translate complex AI and technical concepts into clear, tangible business value; operate as a trusted advisor, not just an implementer.
* Identify and resolve technical blockers proactively; operate with confidence under ambiguity and incomplete information.
* Build reusable engineering assets: integration libraries, prompt templates, and AI workflow scaffolding that scale across the customer base.
* Act as a direct feedback loop from the field to the Product and Engineering teams surfacing patterns, edge cases, and AI feature opportunities discovered during deployments.
* Monitor post-go-live and drive continuous improvement.
Requirements:
3–4+ years of hands-on experience in implementation roles , such as Solution Expert or Implementation Manager, with at least 1 year of hands-on experience implementing and building MCP-based agents and skills
* Strong understanding of MCP architecture and implementation.
* Hands-on experience building AI agents and skills using tools such as Claude and Copilot
* Experience with low-code/no-code automation platforms such as Zapier, Make, and n8n , as well as the ability to develop custom code-based solutions.
* Prior experience in a technical, customer-facing role in SaaS (e.g., forward deployment, solutions engineering, implementation, or technical consulting)
* Proven, in-depth knowledge of CRM systems (Salesforce / HubSpot / Dynamics), ERP and Billing tools
* Strong analytical and systems-thinking skills; comfortable reasoning about data models, integration architecture, and failure modes.
* Excellent communication skills in English — able to present a technical architecture to an engineer and a business case to a VP on the same day.
* Able to juggle multiple complex customer engagements simultaneously without dropping the ball.
* Fluent in English (written and verbal).
* Degree in a relevant field (Computer Science, Information Technology, Industrial Engineering, Information Systems, or equivalent).
This position is open to all candidates.
 
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27/09/2026
Location: Merkaz
Job Type: Full Time
?abra professional services is seeking a Senior Generative AI Engineer! This is a hands-on role combining deep technical expertise with strategic thinking to design, develop, and implement advanced Generative AI solutions. The role offers significant business impact, transforming complex challenges into scalable AI-powered products and solutions used in large-scale production environments. Key Responsibilities: • Lead the end-to-end architecture, design, development, and deployment of advanced Generative AI applications, including Multi-Agent Systems and Retrieval-Augmented Generation (RAG) solutions. • Design and optimize RAG pipelines, integrating Large Language Models (LLMs) with structured and unstructured data, including Knowledge Graphs and Vector Stores. • Build, manage, and automate Generative AI solutions using AWS services, including Bedrock, S3, SageMaker, Lambda, and Step Functions. • Lead Proof of Concepts (POCs) and evaluate emerging GenAI technologies and products to identify the most suitable solutions for business needs. • Integrate AI solutions with existing enterprise systems using APIs and Microservices. • Collaborate with Data Engineers, Analysts, and Product Managers to translate business requirements into scalable and practical AI solutions. • Implement advanced MLOps processes, including CI/CD, Docker, and monitoring solutions, to ensure the reliability, scalability, and maintainability of AI applications.
Requirements:
Requirements • 5+ years of hands-on Python development experience, with expertise in building and deploying AI and Machine Learning applications – mandatory. • Extensive hands-on experience with AWS services relevant to AI/ML, including S3, Glue, Athena, SageMaker, Lambda, and Bedrock – mandatory. • Proven experience with Generative AI frameworks such as LangChain, LlamaIndex, or Haystack – mandatory. • Hands-on experience designing and deploying RAG-based applications, along with practical knowledge of Vector Databases such as Pinecone, Weaviate, or ChromaDB and document indexing techniques – mandatory. • Strong understanding of software development principles, including Git version control, clean code practices, and Unit Testing – mandatory. • Strong analytical and problem-solving skills, with the ability to break down complex business challenges into actionable technical solutions – mandatory. • Excellent communication and collaboration skills, with the ability to clearly explain technical concepts to both technical and non-technical stakeholders – mandatory. Nice to Have: Domain Knowledge: Previous experience in the financial services, fintech, or a related highly-regulated industry. Database Experience: Experience with specialized databases such as graph databases (e.g., Neo4j, Amazon Neptune). MLOps Tools: Familiarity with MLOps platforms beyond AWS, such as Kubeflow or MLflow. Education: A Master's or Ph.D. in Computer Science, AI, or a related field.
This position is open to all candidates.
 
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