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Were looking for a Senior Program Manager to own the execution of our Sovereign AI roadmap end-to-end. Youll sit within the Product group and act as the connective bond between Data Science, Engineering, and Product - making sure complex, cross-functional initiatives ship on time and at the quality bar our customers expect.
If you are an unblocker, enjoy making tough tradeoff calls, and drive accountability across the board, your place is with us. Youll manage multiple parallel workstreams across verticals (Security, Health, AML, and more), platform, and AI/ML domains- and youll be the person everyone relies on to know and manage where things stand and what is about to happen next.
The Dream-Maker Responsibilities
Own and manage the full lifecycle of Sovereign AI projects from planning through delivery. Track milestones, dependencies, and risks across multiple concurrent workstreams.
Drive cross-functional alignment, and work daily with Data Science, Engineering, Product, and Design teams to ensure same direction. Break down silos and surface early mitigation.
Maintain clear, accurate visibility into project status, blockers, and timelines. Communicate proactively to stakeholders and management.
Identify and solve risks, by own and drive resolution.
Work closely with senior leadership and domain leads to ensure roadmap priorities reflect strategic goals.
Translate execution-level realities into clear decision points - when tradeoffs need to be made, you frame the options and drive alignment.
Interface with internal leadership and external government stakeholders to align on scope, timelines, and priorities. Keep information flowing in both directions.
Continuously refine processes, rituals, and tools to make the team more effective without introducing unnecessary overhead.

Were looking for a Senior Product Designer to own the design of how analysts, investigators, and decision-makers interact with complex AI systems in high-stakes, data-dense environments. Youll be the first designer in the Sovereign AI division - which means youll defining standards, update or rebuild the design system, and becoming the teams authority on how users experience our products.
Over time, youll develop deep domain expertise in the investigative and analytical workflows our systems support - and that expertise will make you a critical voice in product and technical decisions. Youll work at the intersection of complex data, AI, and national missions - where every design decision carries real weight. We need someone who takes full ownership, moves with urgency, and proactivly.
The Dream-Maker Responsibilities
Own the design direction - Lead the design vision for the divisions products. Youre not executing someone elses spec - youre shaping what these products look and feel like from the ground up.
Become the domain expert - Develop deep fluency in the investigative, analytical, and decision-support workflows our users rely on. Bring that understanding into every design decision and be the voice of the user in product discussions.
Design for high-stakes environments - Create intuitive, user-centered experiences for mission-critical, AI-driven analytical systems where explainability, auditability, and trust are non-negotiable.
Translate complexity into clarity - Turn complex investigative and analytical workflows into clear, structured product experiences that expert users can rely on.
Build the design foundation - Establish and evolve the design system and design standards for the entire Sovereign AI division. Set the bar for quality and consistency as the team grows.
Collaborate across disciplines - Work closely with product managers, engineers, data scientists, and business stakeholders.
Drive the full lifecycle - From concept and prototyping through execution and postdeployment iteration - you own it end-to-end and push for continuous improvement.
Communicate with impact - Present design rationale and trade-offs clearly to senior stakeholders and cross-functional partners.

As a Cloud Alliance Manager, you will lead and support software vendors to optimize their strategic partnership with the major cloud providers, build a scalable co-sell channel, drive marketing activities, and maximize additional benefits for your customers.

The ideal candidate will lead initiatives to generate and engage with cloud providers (AWS, Microsoft, GCP) to develop new businesses for his/her managed customers. He/she should be able to think strategically when developing a plan and have a demonstrated ability to execute a particular strategy.

Responsibilities
Manage the cloud partnership between our customers, top-tier software vendors, and the hyperscalers GTM and alliance teams.
Promote sales, business development, partnership, and marketing activities for our customers.
Identify partnership opportunities.
Develop new relationships to grow business and help the managed customers expand internationally.
Think strategically when planning and execute the plan effectively and efficiently to ensure customer success.

Required Senior ML Engineer - Applied AI Engineering Group
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-centric technology, representing the pinnacle of computer vision, machine learning, and generative AI within the automotive sector. With over $380.5 in funding and strategic partnerships with industry giants such as Amazon, Hertz, General Motors, Volvo, and CarMax,UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity, encourages teamwork, and strives for excellence.
We are seeking a highly professional Senior Payroll & GL Accountant to manage our comprehensive payroll cycle and daily bookkeeping for our rapidly growing company (140+ employees). This is a dual-focus role requiring expert-level knowledge of Hashavim / Hilan for payroll processing and NetSuite for financial recording and analysis. The ideal candidate will bridge the gap between human resources and finance, ensuring 100% accuracy in employee compensation and financial reporting.
A day in the life and how you’ll make an impact: Execute the end-to-end monthly payroll process using Hashavim , ensuring all 140+ employees are paid accurately and on time.
* Manage all interactions with Israeli authorities (Tax Authority, Bituach Leumi) and pension funds. Ensure correct deductions for pension, study funds (Keren Hishtalmut), and social taxes.
* Handle the complete calculation and reimbursement process for employees on active reserve duty.
* Manage onboarding and offboarding (Form 101, Form 161, and termination settlements).
* Monitor and update attendance records and leave balances.
* Oversee employee benefits, specifically the Cibus (meal card) system.
* Prepare and file annual and periodic reports, including Form 126, 106 and 856.
* Serve as the primary POC for employees, with the ability to address any questions related to payroll.
* Work closely with the HR department on all employee-related financial matters.
* Book and process invoices such as car related, employee meals, communication and other expenses that may be related to employees.
* Record all payroll-related journal entries into NetSuite . Perform monthly reconciliations and provide analytical insights into salary fluctuations and trends.

Our focus is on increasing top-line revenue by building a scalable sales funnel that utilizes the cloud providers solid sales and partnership networks, programs, and brand.

You will be the trusted advisor and hands-on expert guiding our startups through every stage of launching and optimizing their offerings on Cloud Marketplaces, with a primary focus on the AWS Marketplace. Youll combine deep technical knowledge of Marketplace product delivery, fulfillment, enablement with strong business acumen in pricing, private offers, co-selling programs, and GTM strategy.

Your work directly drives client revenue, speeds up time-to-market, and unlocks co-sell opportunities with AWS sales teams.

The role works hand in hand with our internal stakeholders and various contacts within the startup and ISV companies (CTO, product managers, DevOps), and with cloud vendors (Partner Solution Architects, product/service teams).

The ideal candidate will proactively enhance recognition and field awareness of the represented software companies capabilities within the cloud vendor ecosystem.

They must possess strong business acumen, exceptional communication skills in English (both verbal and written), and excellent self-organization and collaboration abilities.

They should also be able to think and explain a strategic level approach while effectively executing hands-on tasks.

Responsibilities
Lead end-to-end AWS Marketplace onboarding and product launches for startups and ISVs (seller registration, tax/banking setup, product metadata, fulfillment methods, metering, entitlements).
Advise on optimal product delivery models (SaaS contracts, AMI, containers, professional services, data products) and technical integration with AWS services.
Develop and execute tailored go-to-market strategies: pricing models, private offers, promotions, listing optimization, and customer acquisition playbooks.
Enable co-selling with AWS: enroll clients in ISV Accelerate, align with Partner Development Managers (PDMs), build co-sell pipelines, leverage AWS co-sell tools, and prepare for joint customer engagements.
Guide clients on Private Offers (PO) and Channel Partner Private Offers post go-live
Conduct workshops, training sessions, and ongoing enablement for client sales, product, and operations teams.
Manage launch projects: timelines, milestones, issue resolution, and post-launch performance optimization.
Stay current on AWS Marketplace features, programs (e.g., ISV Accelerate, PayGo incentives, MDF), and best practices; share insights internally and with clients.
Collaborate with our team on methodology, templates, and tools to scale our service delivery.

Required ML Engineering Team Lead - Applied AI Engineering Group
The Dream Job
It starts with you - a technical leader driven to build both the ML platform and the engineering team behind it. You care about reliable infrastructure, great developer experience, and growing engineers through real ownership. You'll set the technical direction for our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - shaping how models reach production across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments. You stay close enough to the codebase to debug production issues, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the ML platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Set technical direction for the ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - through RFCs, prototypes, design reviews, and build-vs-buy decisions
Lead and grow a team of ML Engineers - hire, mentor, pair on hard problems, and raise the bar through code and design reviews
Contribute to critical systems, debug production issues, and maintain deep context on the codebase to inform technical decisions
Own operational excellence for model serving - set and enforce SLAs, run capacity planning, and keep compute costs predictable
Establish ML engineering standards - reproducible experiments, automated evals, model packaging, CI/CD for models, and observability
Support the full lifecycle of our models - from training on domain-specific data to low-latency inference powering production systems
Work closely with Data Platform, AI, Data Science, and Product teams - translate business priorities into engineering work and manage cross-team dependencies
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as model performance.