דרושים » מוצר » Product Engineer

we are looking for a Senior Full-Stack Engineer.
What You'll Do:
Own features end to end: product conversation → schema → API → UI → how it behaves in production.
Design the systems behind our AI agents - pipelines, orchestration, retries, guardrails, evaluation - so behavior is predictable and explainable.
Build backend services and data models that stay correct and stay fast as volume grows - across shared, single-tenant, and on-prem deployments.
Build the product surfaces our customers and our delivery teams use to configure, monitor, and audit agents.
Own your code in production: CI, deploys, observability, alerting, and the debugging that follows.
Work on how we ship, build and release pipelines, environments, and the infrastructure that lets one codebase deploy into very different customer environments.
Make the call on where complexity is worth it and where things should stay boring.
Raise the bar around you: code review, design review, mentoring, and the standards that keep a codebase alive two years from now.

Required Technical Product Manager - Cloud & Services (Maternity Leave Cover)
About the team:
Our Development Infrastructure group builds the cloud platforms, data services, and AI-powered tooling that our & OEM customers depend on to develop autonomous-driving systems. We are looking for a Technical Product Manager to own cloud and data services used by our internal teams and external customers, alongside a new generation of AI-native, agentic products that bring our proprietary knowledge and self-service tooling directly to engineers.
This is a hands-on technical product role, but not only that. You'll own roadmap, requirements, and cross-functional execution while staying close to the technology itself. Just as importantly, you can zoom out to shape the high-level product story - the vision and the why that align stakeholders and give the work direction. As we increasingly integrate AI into our products, we need a PM who learns fast and turns ideas into working products.
You'll shape how a sophisticated, multi-petabyte data and cloud ecosystem evolves, influencing how our platforms are built internally and how leading global OEMs consume our data and services. It's a rare seat at the intersection of cloud infrastructure, data delivery, and applied GenAI, on products that directly support the future of autonomous mobility.
This is a full-time, 12-month position covering a maternity leave, with potential for extension based on business needs.
What will your job look like?
Own the product strategy and roadmap, partnering with technical leadership to define scope, milestones, and success metrics, and keeping business priorities and engineering execution aligned.
Act as the point of contact for both internal engineering teams and external OEMs - driving requirement definition, prioritization, and ongoing engagement, and owning the lifecycle of feature requests, issues, and escalations.
Lead cross-functional execution across engineering, data, and infrastructure teams, proactively managing dependencies, risks, and delivery timelines while providing clear visibility into product status and outcomes.
Get hands-on with the technology - digging into the products firsthand to see how they behave, test assumptions, and validate solutions before they ship.
Drive our AI-native products - agentic assistants built on MCPs, skills, and retrieval - defining how they surface our proprietary knowledge and automate self-service for engineers.
Lead product releases end to end - planning launches, enabling users, driving adoption, and tracking usage and user engagement to inform the next iteration.
Define product standards and documentation practices - design docs, user guides, and release materials - to ensure clarity, scalability, and operational excellence.

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

As an MLOps Team Leader, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power our AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership.
As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level.
You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers.
Responsibilities
Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies.
Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph.
System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks.
Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment.

We are looking for an experienced, technical, and execution-driven Senior Product Manager (IC role reporting to the VP Product) to take end-to-end ownership of major modules within our complex B2B SaaS ecosystem.

Thriving in a fast-moving startup environment, you will help define the product roadmap and independently drive domain priorities, scoping, execution, and iteration. You will collaborate closely with R&D, Design, GTM teams, and enterprise customers to quickly turn lean concepts into valuable, real-world field solutions.

This is a Product Manager role of the future. We expect you to use AI as a core daily tool, not just an accessory. The right candidate leverages AI to actively expand the traditional PM skillset-independently generating PRDs, UX flows, prototypes, demos, and research summaries to move faster with less dependency on Design, Data, or R&D.

What Youll Do:
Own major product modules end-to-end-from strategy through launch and adoption-and shape the global roadmap while keeping the product scalable and focused.

Break complex enterprise needs into lean, iterative phases (POC, MVP, V1) and write detailed, implementation-ready PRDs, user stories, and UX flows.

Partner closely with R&D and Design to craft intuitive field workflows and make smart tradeoffs between product value, technical complexity, and delivery speed.

Actively use AI tools daily to generate prototypes, PRDs, research summaries, and demos, while helping define, build, and validate AI capabilities within the platform itself.

Deeply understand user needs by analyzing Gong calls, syncing with internal teams, and engaging directly with US enterprise customers through weekly calls and construction site visits.

Collaborate with Sales, Marketing, and Customer Success on positioning and enablement to drive measurable adoption, operational efficiency, and customer value.

we are looking for a Agent Product Manager.
As an Agent Product Manager, you will work directly with enterprise customers to design, deploy, and optimize AI agents tailored to their brand and workflows. Youll own customer outcomes end-to-end, act as the bridge between customers and engineering, and help shape the future of our platform through real-world insights.
What You'll Do:
Design, build, and refine AI agents alongside customers - diving deep into their workflows, challenges, and goals to craft tailored solutions.
Create fast feedback loops with engineering - translating real-world needs into product improvements and new capabilities.
Partner closely with your engineering pod to deliver new features and enhancements that support specific customer use cases.
Own the full lifecycle of customer AI agents - from initial deployment through ongoing optimization and success.
Represent externally - collaborating with enterprise customers, driving key deployments, and showcasing the future of AI-powered CX.

We're looking for a smart and capable DevOps Engineer. You will be part of a small and agile team, working on well-built infrastructure, handling production workloads, building and maintaining infrastructure that supports continuous delivery. This job includes work across the devops stack, including agent development, CI/CD, networking, resource allocation, cloud architecture, security, developer experience, and more.
We work with enterprise customers, with the SLA and expectations that this dictates.
This position includes on-call shifts.
Our stack:
Kubernetes on AWS
Terraform and IAC
Github & Github Actions
Responsibilities
What will you DO:
Design and evolve our cloud multi-region architecture on AWS - networking, interconnects, IAM and high-availability topology - and express it entirely as code with Terraform, following GitOps as a first principle.
Build and own the CI/CD pipelines that plan, review, test and safely apply IaC changes - Policy-as-Code guardrails, drift detection and progressive rollout so infrastructure changes ship as confidently as application code.
Advance Platform-as-a-Product: build self-serve capabilities and paved paths so engineers can provision what they need
Strengthen our observability stack - metrics, logs, traces and alerting.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Design and develop the next generation of AI agents to support higher pace and evolve the RnD productivity while maintaining security and engage the entire company to use AI for better solutions.

The Director of Product Management for Engines owns the strategic vision, roadmap, and execution for our company's scanning engine portfolio across the company One platform. This is the detection technology our customers depend on to find and prioritize risk in their code.
You will lead a team of product managers, set the quality and performance bar across engines, and partner with R&D, Research, Design, and GTM to deliver capabilities that meet enterprise expectations for accuracy, scale, and trust.
How will you make an impact?​
Own the multi-year product strategy and roadmap for the engine portfolio, and make the investment trade-offs across engines that determine where our company competes and wins.
Build and lead a high-performing product management team, setting direction, developing talent, and holding a consistent standard across domains.
Establish detection quality and performance as accountable business outcomes, with clear targets and the evidence to demonstrate progress against them.
Partner with R&D leadership to align engineering capacity and delivery commitments to the roadmap.
Translate customer, market, and competitive insight into a differentiated strategy that drives adoption and revenue growth.
Align GTM, Sales, Marketing, and Customer Success behind the engine narrative, and own its credibility in the market.
Engage enterprise customers and C-level stakeholders to validate direction, build long-term partnerships, and resolve escalations that matter to the business.
Represent the engine strategy internally and externally, including at executive reviews, customer briefings, industry events, and analyst engagements.