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As an AI Product Owner & AI Process and Agentic Designer, you will own the process of transforming complex workflows into scalable AI solutions, bridging the gap between business stakeholders and AI Engineers. You will lead business process analysis, identify agentic process opportunities, validate business value, and define solution designs that enable successful AI implementation across the organization.

Responsibilities

Business Process Analysis & Discovery
Partner with business stakeholders to map, document, and analyze existing workflows, identifying inefficiencies, bottlenecks, and manual processes ripe for automation.
Conduct discovery sessions and workshops to deeply understand business needs, pain points, and success criteria across departments.

Agentic Opportunity Identification
Evaluate workflows to pinpoint where agentic and AI-driven approaches can deliver the most value, distinguishing tasks suited to automation, augmentation, or full agentic orchestration.
Maintain a prioritized pipeline of AI/agentic opportunities, assessing each for feasibility, complexity, and impact.

Business Value Validation
Define and quantify the expected business value of proposed solutions (e.g., cost savings, time reduction, quality improvement, revenue impact) and build the business case for investment.
Establish success metrics and KPIs, and track realized value post-implementation to ensure outcomes match projections.

Solution Design & Definition
Translate business requirements into clear solution designs, including agentic process flows, decision logic, data inputs/outputs, integration points, and human-in-the-loop checkpoints.
Define guardrails, escalation paths, and fallback behaviors to ensure solutions operate safely and reliably.
Stakeholder & Engineering Bridging
Serve as the primary liaison between business stakeholders and AI engineers, translating business intent into technical requirements and engineering constraints back into business terms.
Own the product backlog, prioritize features, and clearly communicate scope, trade-offs, and timelines to all parties.

Implementation Enablement & Iteration
Guide solutions through the full lifecycle from concept to deployment, supporting testing, validation, and change management.
Gather feedback, monitor performance, and drive continuous refinement of deployed AI and agentic solutions.

Scalability & Standardization
Identify reusable patterns, components, and best practices to scale successful solutions across the organization.
Contribute to governance frameworks, documentation standards, and design principles for AI/agentic product development.

Required Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect within the Co-design team, you will serve as a technical lead bridging model architecture innovation and next-generation hardware design. Operating at the highest levels of AI research and engineering, you will define the goal and architectural roadmap for our future machine learning serving and training capabilities. You will guide the integration of ML research such as massive-scale foundation models with advanced silicon architectures to create industry-leading, high-performance, and power-efficient accelerators.
Responsibilities
Define and drive the technical roadmap and architecture for the hardware/software stack to ensure exceptional performance for ML models. Act as the technical liaison across research, software, and hardware teams, steering model architecture innovation to maximize scaling, quality, and hardware efficiency.
Architect next-generation configurable simulation frameworks and performance models, setting the organizational standard for evaluating complex microarchitectural decisions. Drive high-stakes choices regarding Power, Performance, Area (PPA) and buildability for future chip and system architectures, expertly balancing long-term technological trends with strict product delivery timelines.
Guide system-level performance analysis across highly distributed ML systems, innovating new methodologies to optimize and balance compute, memory bandwidth, and inter-chip network requirements. Their leadership will directly shape the future of high-performance AI infrastructure and hardware-software co-design.
Manage cross-functional partnerships across hardware, compiler development and ML teams.

We are building a new team focused on redefining the future of code analysis infrastructure, combining advanced GenAI techniques with deep static code analysis. We're looking for a highly motivated Agentic code analysis engineer to join us on this mission.
We're working in a hybrid model: 3 days in the office, 2 days from home.

You are invited to meet the R&D team here!

In this role, you will:

Research and develop next-gen code analysis and remediation algorithms

Work hands-on with GenAI models and integrate them into detection workflows

Tackle complex software analysis problems (e.g., call graphs, control/data/taint flow analysis)

Collaborate closely with Product Managers, Algorithm software engineers and application software engineers to prototype, validate, and productize your innovations

Responsibilities:

Design and implement machine learning and algorithmic solutions for code analysis

Build GenAI-powered developer tools for static and semantic code analysis

Enhance our existing detection infrastructure with intelligent, context-aware insights

Translate cutting-edge research into practical, scalable product features

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

Are you a master of the AI lifecycle who can thrive at the intersection of deep learning research, cybersecurity and large-scale production systems? Do you possess the rare ability to jump into a complex technical crisis, diagnose a bottleneck in a Small Language Model (SLM), and lead a team to a production-ready solution?
As a Distinguished AI/ML Architect, you will be the premier technical authority across the Cortex AI/ML organization. You will serve as the "force multiplier" for multiple AI & ML teams, ensuring that our AI strategy - from endpoint-deployed DL/ML models to cloud-scale agentic products - is executed with world-class precision. You will operate as the primary technical architect and hands-on leader for our most ambitious and difficult initiatives.
Key Responsibilities
Operate at the forefront of AI and cybersecurity, leveraging vast datasets to design and deploy innovative defense mechanisms.
Provide horizontal technical leadership across endpoint, cloud, and agentic AI teams to ensure architectural excellence.
Oversee the design and deployment of different model architectures to guarantee scalability and high-performance standards.
Spearhead high-difficulty initiatives and new research frontiers, moving them from ambiguity to production.
Resolve complex technical bottlenecks across the stack, optimizing model efficiency and runtime performance.
Align research and engineering efforts to transform advanced models into robust, production-grade products.

we are looking for a AI Adoption Engineer.
Responsibilities:
1. Use Case Discovery & Prioritization
Embed with non-R&D teams (CS, Sales, Marketing, Finance, HR, Operations) to understand workflows and identify where AI creates the highest leverage.
Define and prioritize whats worth building, maintaining a live backlog aligned with VP of AI.
Good discovery is the difference between automation that gets used and automation that gets ignored.
2. AI Tool Development & Delivery (~40%)
Build custom tools, workflow automations, Cowork skills, and AI integrations with existing business systems.
Validate with real users, iterate on adoption signals, and transition stable tools to team ownership.
This role leads by shipping. Working tools - not proposals - are the primary output.
3. Enablement & Adoption
Ensure tools get used: onboarding sessions, playbooks, and hands-on support through behavior change.
Build team confidence and self-sufficiency over time; avoid creating dependency on a single person.
4. AI Landscape Awareness
Evaluate new models, tools, and capabilities for internal relevance and bring what matters back to Navina.
Collaborate with VP of AI to maintain a current roadmap for internal AI operations.

we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

The Prisma Browser group is building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
Prisma Browser is an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.

Responsibilities
Take full end-to-end ownership of features - from product thinking and design through development, testing, deployment, and post-production monitoring.
Collaborate with cross-functional teams to design, develop, and deploy high-quality web applications and services.
Champion and apply agentic development practices, leveraging AI-assisted tooling and automation to accelerate R&D velocity.
Develop robust and scalable systems using Node.js,C#,React, TypeScript and related frameworks.
Own the full DevOps lifecycle - CI/CD pipelines, containerization, release management, and production observability.
Optimize web applications for performance, scalability, and security across both microservice and monolithic architectures.
Write and maintain automated tests (unit, integration, end-to-end) to ensure code quality and reliability.
Utilize version control systems, particularly Git, for code management and collaboration.
Stay current with emerging technologies, AI tooling, and modern engineering trend.

We are seeking a skilled versatile software engineer with a vast experience in enterprise business applications development (like: Salesforce, NetSuite etc.) that will be part of the business applications development team and will also have a deep understanding of enterprise grade AI development and implementation, specifically, but not limited to, Microsoft 365 AI tools , Microsoft applications building tools, Claude tools and working with various AI models.
The ideal candidate will design, implement, and optimize business solutions and AI solutions that enhance Cellebrite business processes, productivity and collaboration across our organization.
Key Responsibilities:
Design, develop, and deploy business applications solutions and AI-driven solutions integrated with enterprise business systems.
Partner with IT analysts and business stakeholders to understand requirements, and translate them into scalable technical solutions, that deliver measurable business impact.
Build and integrate LLM-based solutions (e.g., OpenAI, Anthropic, AWS Bedrock), including coding, orchestration workflows using tools such as LangChain, n8n, or similar frameworks.
Own the end-to-end lifecycle of business applications and AI solutions -from prototyping and experimentation to production deployment, monitoring, maintenance & support and continuous optimization.
Integrate and enhance enterprise platforms (e.g., Salesforce, NetSuite, iPaaS services) with AI capabilities to improve business processes.
Evaluate, adopt, and standardize AI tools, frameworks, and best practices, while staying current with emerging technologies and proactively being part of a continuous innovation.
Maintenance and support - handling relevant tickets and bugs within defined SLA and customer satisfaction targets.

we are looking for an AI Specialist with deep, hands-on expertise in modern AI platforms to train, prototype, build and ship AI-powered solutions across the organization. Working closely with business stakeholders and IT peers , this role is a combination of an ability to design and work with AI consumers across the organization and technical - to turn the business needs into working AI solutions at speed using the latest agentic and low-code AI tools.
In this role you will also nurture the AI builder's community with advanced knowledge, technical sessions, builders CI/CD process support, creating business data foundations and literacy and responsible AI training and practices
Responsibilities:
Rapidly prototype and deliver working proof-of-concepts and working builds that translate business requirements into functional solutions, iterating quickly toward production.
Lead advanced, in-depth technical sessions, workshops, and hands-on labs for technical and semi-technical audiences, building internal capability in AI-assisted development.
Build and optimize agentic workflows, tool integrations, to maximize solution capability and reliability.
Establish and promote best practices for AI-assisted development, code quality, reusability, and responsible build standards across teams.
Drive build projects from concept through delivery, ensuring quality, performance, and maintainability.
Collaborate with Business Applications, IT R&D, Analytics and business units to identify high-impact opportunities and deliver measurable value through custom-built AI solutions.
This includes identification of required foundations to support the builders community (literacy, business models, RBAC foundations etc.)
Stay continuously current with the fast-moving AI development landscape - new models, platforms, agent frameworks, and tooling - and bring that knowledge into the organization.
Ensure compliance with corporate information security standards, data handling, and governance policies.

We're looking for an experienced AI Security Architect to join the Security Architecture team.
As a AI Security Architect, you'll design and govern enterprise AI security frameworks, define controls for AI/ML platforms and LLM deployments, and drive secure AI adoption in close collaboration with engineering, business units, and data teams.
You'll own security architecture reviews, threat modeling, and risk assessments across the full AI lifecycle - from development through production.
Key Responsibilities:
Design, develop, and maintain enterprise AI security architectures, frameworks, standards, and policies
Define and implement security controls for AI/ML platforms, LLM deployments, AI-enabled applications, and supporting infrastructure
Establish security requirements and best practices for AI development, deployment, and operational processes
Assess AI-related risks and ensure alignment with corporate security standards, regulatory requirements, and industry best practices
Collaborate with IT, cloud, data, and security teams to ensure secure deployment of AI solutions across the organization
Familiarity with AI coding assistants, autonomous agents, LLM frameworks, and orchestration systems

We are building a cutting-edge GenAI-powered SaaS platform that enables investigators to interact with complex case data through a conversational interface. The system leverages LLMs, RAG architectures, and agentic workflows in a rapidly evolving environment.
As we scale, we are looking for a hands-on R&D Manager, reporting to the VP R&D, to take ownership of day-to-day execution, team delivery, and production stability - enabling the team to move fast while freeing leadership to focus on new innovation and strategic initiatives.
This is not a traditional management role. You will operate as a player-coach, staying close to the technology while leading a small, high-impact team.
Key Responsibilities:
Lead the day-to-day execution of the development team (planning, prioritization, delivery)
Work closely with Product, DevOps, and Customer Success to ensure smooth delivery of features and fixes
Own production stability and ongoing support processes (triage, prioritization, resolution tracking)
Manage and mentor engineers while maintaining a flat, startup-like culture
Drive high engineering standards across code quality, testing, and system reliability
Stay hands-on with the system architecture, especially around GenAI pipelines, RAG, and agentic flows
Remove blockers and ensure the team can execute quickly in a fast-changing environment
Balance short-term delivery needs with longer-term technical health
Improve development processes without introducing unnecessary overhead