דרושים » אינטרנט ודיגיטל » Director of AI Enablement

This role sits at the intersection of customers, Engineering, Data Science, GIS, Sales, Marketing, and Customer Success. You will translate validated market needs into scalable products, clear technical requirements, and prioritized roadmaps.

The ideal candidate combines strong product strategy, technical fluency, customer discovery, and hands-on product ownership, with experience building B2B technology products in data-rich or infrastructure environments.



Key Responsibilities


Product Strategy & Roadmap

Own and evolve the product roadmap in line with company and revenue goals.
Shape the positioning and evolution of Recover, EarthWorks, EO Discover, and future SaaS, DaaS, API, and AI offerings.
Prioritize scalable, recurring product opportunities over one-off customer requests.
Build business cases and define product KPIs to support investment and prioritization decisions.


Customer & Market Discovery

Conduct structured Voice of Customer research with utilities, engineering firms, agencies, and partners.
Translate customer workflows into clear problem statements, personas, and Jobs-to-be-Done.
Validate concepts through prototypes, MVPs, pilots, and market feedback.
Assess market size, adoption potential, and willingness to pay.


Product Ownership & Delivery

Translate strategy into epics, features, user stories, and acceptance criteria.
Own and prioritize the backlog based on customer value, strategic fit, dependencies, and effort.
Partner closely with Engineering, Data Science, UX, and GIS through planning, refinement, development, and release.
Coordinate UAT, define release criteria, and ensure clear traceability from customer problem to measured outcome.


Technical Product Leadership

Work across SaaS, cloud platforms, APIs, integrations, AI/ML, geospatial analytics, remote sensing, and SAR.
Translate technical capabilities into customer-facing products and workflows.
Understand architecture, data flows, integrations, and technical trade-offs well enough to work effectively with R&D.
Challenge technology-led development that lacks clear customer or market value.


Go-to-Market & Product Performance

Partner with Marketing, Sales, and Customer Success on ICPs, packaging, pricing, positioning, launches, pilots, and POCs.
Support strategic customer and partner engagements.
Track product success through adoption, retention, revenue, customer value, quality, and time-to-value.
Use customer feedback, product usage, and competitive insights to drive continuous improvement.


Product Operations

Improve intake, prioritization, release-management, and product governance processes.
Build practical templates and dashboards for roadmaps, business cases, launches, and product performance.
Strengthen coordination across Product, Engineering, Operations, Sales, Marketing, and Customer Success.

we are looking for a hands-on technical leader to build and operate a secure local large-language-model platform for the company. The platform will allow engineering and business teams to use generative AI with proprietary source code, product documentation, technical standards, test artifacts, support knowledge, and other approved internal data while keeping sensitive information within company-controlled environments.
This is a senior individual-contributor role spanning applied LLM engineering, platform architecture, search and data pipelines, security, and production operations. You will turn promising prototypes into a dependable internal capability: selecting and optimizing open-weight models, building permission-aware retrieval, creating reusable APIs and tools, integrating with existing engineering workflows, and establishing objective ways to measure quality, safety, latency, capacity, and business value.
The successful candidate will understand that a useful enterprise LLM is more than a model and a chat interface. It requires trustworthy source grounding, strong access controls, repeatable evaluation, careful tool permissions, observable production services, and an operating model that keeps data, indexes, prompts, models, and dependencies current. You will make pragmatic build-versus-buy decisions and choose the simplest approach-search, retrieval-augmented generation (RAG), prompting, workflow automation, or model adaptation-that meets each use case.
Initial use cases may include engineering knowledge discovery, source-code understanding, troubleshooting assistance, technical-document Q&A and summarization, test and log analysis, and drafting structured engineering artifacts. The platform should be extensible to additional approved use cases as needs and model capabilities evolve.

The Senior Product Manager, SW Platform / Enablement will lead the direction and roadmap execution for shared platform capabilities that help CathWorks solutions scale across cath labs worldwide, including infrastructure, connectivity, cloud enablement, shared services, and efficient clinical software development.
You will partner with engineering, architecture, cybersecurity, quality, regulatory, clinical, commercial, and product teams to turn platform needs into clear requirements and priorities aligned with business, roadmap, technical, and regulatory goals.
The ideal candidate brings strong product ownership, technical curiosity, and practical experience with software infrastructure, cloud technologies, and Agile delivery, with the ability to discuss complex topics with engineering and communicate platform value to stakeholders.
Responsibilities may include the following and other duties may be assigned:

Own the roadmap for shared software platform capabilities across products and applications. Lead platform features for infrastructure, connectivity, cloud enablement, shared services, and scalability. Improve reuse, interoperability, development efficiency, and technical sustainability. Translate platform strategy into requirements, priorities, and measurable outcomes. Balance near-term delivery with long-term platform architecture goals
Own platform requirements from concept through release and learning. Define user needs, requirements, acceptance criteria, and release scope
Prioritize and manage the platform backlog with Agile teams. Support roadmap, release, sprint planning, backlog refinement, and feature acceptance. Track adoption, performance, risks, and business impact
Partner with engineering and architecture to define scalable, secure software infrastructure. Define connectivity, data flow, integration, and cloud platform services. Support platform decisions for future products, ecosystems, and multi-application growth. Translate technical constraints into product tradeoffs and priorities
Partner with engineering, architecture, cybersecurity, quality, regulatory, clinical, commercial, and product teams. Represent product in roadmap, Agile, design review, and release readiness forums. Align teams on priorities, dependencies, risks, sequencing, and delivery plans. Communicate platform direction to technical and non-technical audiences
Document platform requirements and decisions per quality, regulatory, and cybersecurity. Support Agile execution and applicable product development processes
Contribute to roadmap governance, release reviews, and cross-functional decisions. Manage risks, dependencies, mitigation plans, and escalations for platform initiatives.

We are looking for a hands-on Senior Applied AI Evaluation Engineer to improve how our RAN R&D organization analyzes engineering tickets, supports Root-Cause Analysis, recommends ownership, and learns from resolved cases.
You will build rigorous evaluation datasets, establish meaningful baselines, compare internal and approved external tools, analyze failure modes, and prototype improvements across retrieval, classification, prompting, agent workflows, and model selection.
This role is focused on measurable, evidence-based improvement rather than AI demonstrations. You will assess whether AI-generated conclusions are accurate, grounded in evidence, appropriately calibrated, and useful to engineering teams.
As a secondary area of focus, you will analyze engineering workflows at case and team level to identify bottlenecks, handoffs, dependencies, and opportunities for process improvement.

We are looking for a hands-on Computer Vision & AI Algorithm Engineer to develop advanced imaging algorithms for a cutting-edge medical device. The role spans the full spectrum of algorithm development - from creating new solutions to improving, maintaining, validating, and integrating them into the product. The ideal candidate is curious, pragmatic, and comfortable moving between deep learning, classical computer vision, data analysis, debugging, validation, and product integration as needed. They measure success by seeing algorithms work reliably in a real-world product and enjoy collaborating across disciplines to solve the challenges that move the product forward.

Responsibilities may include the following and other duties may be assigned:
Design, develop, maintain, and continuously improve AI, computer vision and image processing algorithms for a medical imaging product.
Own the full lifecycle of algorithm development, from concept and data definition through implementation, validation, product integration, and long-term maintenance.
Use both classical computer vision methods and machine/deep learning methods to come up with solutions for various problems in the domains of image classification, segmentation and 3D modeling.
Collaborate with SW developers, biomedical engineers, product specialists and other algorithms developers to refine and enhance existing applications.
Maintain and improve algorithm robustness, performance and reliability in production environments.
Identify opportunities for innovation and design novel algorithms to address complex technical challenges.
Stay at the forefront of relevant academic research by reviewing the latest papers and evaluating their potential impact on the companys algorithmic stack.