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Were growing fast and looking for a talented and passionate Engineering Team Leader to join us!

Were looking for a passionate and impact-driven Product Manager to join HR Planning group and lead our Workforce Planning module. Workforce Planning is a key part of vision to deliver a seamless, strategic, and data-driven HR platform. This role will be central to shaping how organizations plan their workforce, manage positions and headcount, align people plans with business priorities, and make better decisions through clear, reliable data.
As the Product Manager for Workforce Planning, youll lead high-impact initiatives that connect across platform and empower HR leaders, finance teams, workforce planners, and managers to collaborate more effectively. Youll own the product strategy, delivery, adoption, and measurable business outcomes, helping customers build scalable, transparent, and efficient workforce planning processes.


Job requirements
What you should have:
4+ years of experience as a Product Manager, with a track record of owning and delivering product roadmaps in B2B SaaS environments.
Strong strategic thinking and analytical skills, with the ability to define KPIs, connect features to business impact, and drive prioritization decisions based on data and user feedback.
Excellent cross-functional collaboration and leadership skills - able to align across R&D, Design, Product Marketing, and GTM teams.
Proven ability to lead execution, resolve ambiguity, and deliver impactful outcomes in complex and fast-paced environments.
Exceptional communication and storytelling abilities, with a talent for clearly articulating product decisions and value to a wide range of stakeholders.
A proactive and customer-obsessed mindset, with hands-on experience conducting user research and analyzing behavioral data.
Experience working in HRTech, FinTech, or data-intensive products is a strong advantage.
Full professional proficiency in Hebrew and English - required.

Responsibilities
What you'll be doing:
Most of your time will be spent delivering business value across our stack
We work closely with Product and Risk, and expect engineers to be part of the conversation from problem definition through delivery.

That means things like:
- Working directly with Product, Risk and other stakeholders to understand the problem, challenge assumptions, and design pragmatic solutions.
- Taking ownership of features from initial discussions through production rollout.
- Identifying opportunities to simplify, automate or improve the system.
- Helping the team evolve through design discussions, code reviews and technical direction.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy:
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering:
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering:
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership:
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

As a Marketing Manager, you will turn strategy into execution across campaigns, content, and product storytelling.

Working closely with the VP of Marketing, Director of Product Marketing, and cross-functional teams, you'll own day-to-day marketing initiatives that drive awareness, pipeline, and product adoption.

This role is ideal for someone who thrives in a fast-paced environment, enjoys building and shipping, and knows how to translate complex product capabilities into clear, compelling narratives that resonate with finance and operations leaders.

You'll play a key role in shaping how our products show up in the market across our website, campaigns, launches, events, PR, and partner channels.

Responsibilities
Content & Social Media

Create and manage high-quality marketing content (landing pages, blogs, reports, etc.)
Create and manage social media content that reinforces product positioning, builds brand credibility, and drives awareness, while continuously testing and optimizing performance.
Collaborate with Demand Gen to develop and launch high-impact campaign assets that drive pipeline

Website Experience
Own and continuously improve the website as a core growth channel, ensuring pages and key journeys are clear, up to date, and optimized for conversion. Collaborate with Product, Design, and Demand Gen to launch new pages, test messaging and layouts, and use data and AI tools to improve performance and user experience.

Email marketing
Plan and execute targeted email campaigns across the funnel from event promotions to lifecycle and nurture sequences, optimizing for engagement and conversion.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy:
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering:
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering:
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership:
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a Senior Product Engineer to join a global team of a Product Engineers that own a technical success and customer satisfaction across multiple high-impact projects. This role is deeply rooted in data analytics; youll be working at the intersection of silicon, systems, and software to deliver high-value insights to customers.

Responsibilities
Performing post-silicon and system-level data analysis and providing insights on data extracted from post-silicon stages.
Supporting customers with analytics platform problems solving and new features introduction.
Drive integration of proteanTecs analytics platform within customer environments, bridging silicon, test, and system-level domains.
Collaborate with R&D and data science teams to develop, validate, and improve advanced analytics algorithms.
Troubleshoot complex silicon/system issues through data-driven insights.
Partner with internal stakeholders (design, software, product) to influence roadmap and execution.
Act as a technical professional in customer onboarding, support, and ongoing engagement.

we are seeking a Lead System Architect to join our system architecture team and help define NR-NEXUS, our next-generation AI inference platform.

Responsibilities

Lead the software architecture and technical roadmap for NR-Nexus
Write system specifications for NR-Nexus product
Research AI infrastructure, SaaS platforms, model serving, and inference trends
Work with engineering to translate technical capabilities into product value
Work closely with engineering teams to optimize performance, scalability, and feature delivery.
Define performance goals and lead profiling, benchmarking, and optimization efforts for GenAI and distributed AI workloads.
Collaborate with customers, partners, and open-source communities to ensure ecosystem compatibility and adoption.
Mentor software engineers and provide technical leadership

We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software.

Location: Tel-Aviv in hybrid model.

Responsibilities
Develop advanced ML algorithms using data from proteanTecs Agents embedded in silicon. Example domains include:
Lifetime predictions.
Clustering and dimensionality reduction.
Parametric modeling and screening.
Time-series forecasting.
Lead end-to-end algorithm lifecycle: ideation - research - POC - design - implementation - validation - deployment.
Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions.
Drive integration of AI-enhanced tools and intelligent pipelines into ML workflows.

A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.

***This is not a Data Science position***

Responsibilities:

Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines