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As a Wireless Design Verification Engineer, you will be part of a team that is responsible for pre-silicon RTL verification of communication subsystems, SoC sub-systems and chip-level functionality. The activity may focus on block level, sub-system level or chip level, including end-to-end simulations of the entire data/control path. You will interact with DV methodologists, designers and communication systems engineers to develop reusable testbench and verification environment deploying the latest methodology with metric driven verification.
Description
- Own critical block and sub-system verification of wireless SoC projects
- Architect and develop testbenches and environments, by using state-of-the-art verification methodologies
- Define verification plan, create, simulate and debug test scenarios
- Drive regression and coverage analysis to ensure high quality DV
- Collaborate with design and systems engineering teams to review requirements, specifications and architecture, extract features and define DV attribute

Responsibilities
Design, develop, and maintain full stack features end-to-end-from frontend UI (Angular) through backend services (.NET / Node.js) to database and infrastructure.
Build and iterate on AI-powered product capabilities, including LLM-based coaching, conversation simulations, and intelligent analytics.
Work with LLM orchestration frameworks (e.g., LangGraph, LangChain) and cloud AI services (AWS Bedrock, OpenAI, Anthropic) to design reliable, production-ready AI pipelines.
Collaborate closely with product managers, designers, and backend engineers to translate requirements into high-quality, scalable solutions.
Design and develop responsive, performant frontend experiences using Angular, TypeScript, and modern component libraries.
Own the quality of your work-write tests, conduct code reviews, and continuously improve the codebase.
Evaluate and integrate new technologies, tools, and architectural patterns to keep our stack modern and efficient.
Troubleshoot and resolve complex technical issues across the full stack, including performance bottlenecks and integration challenges.

We are looking for a Senior SW, full-stack Developer
To lead technical efforts and develop core components of our platform
Take part it architectural decisions and implementations.

we are looking for a AI Architect.
Responsibilities
1. AI Architecture & Technical Leadership
Guide AI architectural direction across 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 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.

We're looking for a Technical Account Manager to join our growing team and serve as trusted advisors to our customers. As a TAM, youll play a critical role in driving customer success by combining your technical expertise with your passion for customer engagement. Youll guide customers through onboarding, help them maximize value from our platform, and ensure their long-term satisfaction and retention.
While the primary focus of this role is post-sales, you will also support pre-sales activities, partnering with the sales team on technical deep-dives, product demonstrations, and proof-of-value engagements to help win new business.
Responsibilities
Build strong relationships with customers and become their primary point of contact for technical matters
Own the post-sales technical relationship, ensuring successful onboarding, implementation, and ongoing usage
Provide technical guidance, conduct training sessions, and lead workshops to help customers get the most out of our platform
Deeply understand customer architecture and workflows, offering proactive recommendations and best practices
Act as the voice of the customer internally, working closely with Product, Engineering, and Support teams
Monitor account health, identify risks, and proactively drive resolutions
Partner with the sales team on technical evaluations, product demonstrations, and proof-of-value engagements
Serve as a technical resource during prospect meetings, addressing architecture and security questions
Help craft tailored proposals and technical solutions that align with prospect requirements.

We are a well-funded cybersecurity startup backed by top-tier VCs. Our mission is to solve some of the most challenging problems in the security of software- how to make AI-first organizations release applications fast and not be bothered by security, leveraging AI agents to create secure code and fix vulnerabilities.
We are in a fast-growing, new space and looking to lead this new era of application security where AI write code.
The Role
We are looking for an experienced Development Team Lead to lead a team of talented engineers building core components of our platform.
This is a hands-on leadership role combining technical ownership, people management, and architectural decision-making. You will lead a team of engineers, drive execution of complex projects, and help scale both the technology and the team.
Responsibilities
Lead and mentor a team of software engineers, fostering technical excellence and ownership
Drive the design, architecture, and development of scalable cloud-native services
Collaborate with product, security, and platform teams to deliver high-impact features
Maintain high engineering standards including code quality, testing, and system reliability
Take an active role in hands-on development and technical problem solving
Support team growth through mentoring, feedback, and hiring.

We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What Youll Do:
Data Quality & Validation:
Design and execute data validation strategies for large-scale batch and streaming pipelines
Ensure data correctness, completeness, freshness, and consistency across the data lake
Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing:
Plan and execute performance and scalability tests for data pipelines and processing jobs
Identify bottlenecks across ingestion, transformation, and querying layers
Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure:
Develop and maintain the data teams QA automation infrastructure
Build reusable testing frameworks and tools tailored for large datasets and pipelines
Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership:
Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication:
Champion a quality-first culture within the team
Clearly communicate risks, findings, and quality metrics to technical stakeholders
Balance thoroughness with pragmatism in fast-moving, high-scale environments.

Required AI Platform Engineer
Position Overview:
We're assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As an AI Platfrom Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
Build advanced AI platform that operates both as a cloud SaaS and as a fully self-contained on-prem / edge deployment, designed for privacy-sensitive and security-critical environments, at the intersection of backend development, AI integration, DevOps, and open-source systems engineering.
You will be part of the core team responsible for adapting, hardening, and operating our SaaS architecture in on-prem and single-node environments (on Prem servers, laptops). Working closely with architecture and product management and play a key role in making complex AI systems deployable, reliable, and operable outside the cloud.
Key Responsibilities
Platform & Application Engineering:
Adapt cloud-native AI services to on-prem and edge deployments (single node, no managed cloud services).
Build and maintain full-stack components: Backend APIs (Python / Node.js), Lightweight UIs or internal tools when needed, Ensure services are stateless, configurable, and portable across environments.
AI & Open-Source Integration:
Integrate and operate open-source LLMs for:
RAG pipelines
Agentic workflows
Tool calling and orchestration
Work with: Embedding models, Vector databases (local and embedded modes), Analytical engines (e.g., embedded SQL / columnar systems), Optimize inference for CPU / single-GPU environments (quantization, batching, caching).
DevOps & Runtime Engineering (Strong Focus):
Package services into portable Docker containers usable in:
On-prem servers (Kubernetes)
laptop / edge devices
Implement in-process scaling strategies (worker pools, task queues, batching).
Build simple, reliable deployment and startup flows (no heavy orchestration).
Manage configuration, secrets, logging, and observability in constrained environments.
Systems & Reliability:
Design for: Offline operation, Limited resources, Predictable performance
Implement graceful degradation between: SaaS mode, On-prem server mode, Single-node / laptop device mode, Debug complex interactions across AI models, storage, and runtime systems.

We are looking for B.A. / B.Sc. / M.A. / M.Sc. students with at least 1.5 years (a minimum of 3 semesters) remaining in their studies, who are available to work 3.5-4 days per week. Please note that this position is not focused on Machine Learning engineering. Decision scientists Interns are highly motivated team players with strong analytical skills. Our Decision Scientists specialize in creating, driving, and executing initiatives to mitigate fraud on our companys platform and improve the experience for our companys hundreds of millions of customers while guaranteeing compliance with regulations. Our Decision Scientists specialize in analysing user behaviours, creating and leveraging advanced proprietary risk management mechanisms. as an intern, you will overcome challenges presented by big data, evolving fraud techniques, new payment technologies and human behaviour.
Job Description:
Your day to day
In your role as a Decision Scientist Intern, you will:
Master our companys data warehouse to help gain insights into consumer risk
Perform data-driven behaviour research
Transform results into business cases
Develop and own data-driven risk decision strategies to support our companys global financial business goals
Measure performance against KPIs and goals
Close collaboration with partners and stakeholders in Risk and in our company to execute our companys long-term strategy
What Do You Need To Bring-
Education: student status required Bachelor / Master
Student status - 2 years remaining before graduation, preferably in one of the following: engineering, computer science, math, physics, statistics, economy, accounting, business, cognitive science, medicine
Availability for 50% position or more
Some experience with SQL and Excel
Some experience with programming / R / Python / BI tools - advantage
Excellent spoken and written English
Quick-thinker, fast learner, problem solver
Team worker, responsible and trustworthy
People person - ability to communicate and motivate
We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.

Were looking for a highly skilled AI Engineer to join our Forensic Research Group and help shape the next generation of intelligent forensic platforms.
Youll work at the intersection of Generative AI, agentic systems, and real-world data, building advanced capabilities for both internal tools and production systems that transform how complex data is analyzed and understood.
Using state-of-the-art models and emerging AI paradigms, youll design systems that move beyond traditional pipelines into autonomous, adaptive workflows.
Youll help define the future of agentic decoding - where AI doesnt just assist, but actively reason, explore, and uncover critical evidence, impacting millions of cases worldwide.
If youre excited about building impactful AI systems and solving complex, messy problems, this role is for you.
What Youll Do:
Design and build AI-driven and agentic solutions to parse, analyze, and interpret data from forensic extractions (including mobile devices)
Develop GenAI-powered capabilities for understanding, structuring, and reasoning over unstructured data
Combine LLMs, multi-agent systems, and heuristic approaches to improve data identification, classification, and insight generation
Build autonomous and semi-autonomous pipelines that transform manual and brittle workflows into scalable, intelligent systems
Work with real-world, noisy datasets to uncover patterns, anomalies, and meaningful structures
Collaborate closely with forensic researchers and engineers to translate domain expertise into AI-native solutions
Influence system architecture, tooling, and the evolution of internal AI platforms and agent frameworks
Evaluate, fine-tune, and integrate state-of-the-art models (LLMs, multimodal models, etc.) for complex real-world problems.

Required AI Architect
Position Overview:
As the AI Architect for our SaaS Platform & Products, you will define and drive the end-to-end AI architecture that powers our cloud AI platform and product capabilities, while ensuring strong alignment with security, privacy, reliability and cost-efficiency requirements. You will partner closely with engineering leaders, product management, data science, security and operations to translate business needs into a scalable, governed and AI platform that accelerates innovation across multiple product lines.
This is a hands-on architecture role: you will set technical direction, run architectural reviews, and build prototypes to validate technology choices and de-risk delivery.
Key Responsibilities:
Own the AI Vision: Take end-to-end ownership of the AI architecture across, including our cloud AI platform, agentic AI infrastructure, and on-prem/hybrid AI deployments.
Architect an AI Platform for SaaS Products: Define reference architectures and shared building blocks (e.g., AI gateways, orchestration runtimes, memory/RAG systems, vector search, evaluation frameworks, observability, and guardrails) that can be adopted consistently across products and teams.
Cost Optimization and Scalability: Provide architectural leadership to ensure AI systems are designed for cost efficiency and scalability, actively identify and implement opportunities to optimize cloud spend (FinOps), improve utilization, and meet latency/SLO targets.
Product-Centric Collaboration: Collaborate with engineering, product, data science, security, and operations teams to translate product requirements and business needs into a strategic AI architecture that drives measurable product value.
Technology Evolution and Prototyping: Evaluate new technologies, tools, and methodologies to continuously improve our AI systems, build prototypes and proof-of-concepts to validate approaches and accelerate decision-making.
Technical Reviews, Standards and Mentorship: Lead technical design reviews and provide guidance on best practices and emerging technologies. Act as a technical authority and mentor, fostering a culture of engineering excellence and pragmatic delivery.
AI Governance, Privacy and Security: Ensure AI capabilities comply with data privacy, security, and ethical AI guidelines. Partner with security and legal stakeholders to implement governance controls and risk mitigations appropriate for regulated environments.

We're seeking a talented, versatile, and highly independent Full Stack Engineer to join our engineering team.You will drive end-to-end development of technical foundation and platform services that empower all of our teams, influencing both product capabilities and technical decisions.
Responsibilities:
Lead development processes from ideation to production
Develop, implement, and maintain the platform's foundational services, including web applications, APIs, and essential internal solutions.
Collaborate with multiple engineering teams, product, and medical teams across the organization
Build a customer-centric product with a deep understanding of the complex healthcare industry

We're hiring for a new AI Engineering team in Tel Aviv, and you would be the first infrastructure hire. You will own the platform layer for AI agents the team builds: deployment architecture, observability, and production reliability.
The team's first two projects: an agent that automates internal governance processes (vendor reviews, security questionnaires, tool provisioning), and an agent that helps engineering teams prepare for architecture reviews. Both integrate with external APIs (LLM providers, OneTrust, ServiceNow), handle structured decision logic, and manage sensitive data flows with audit requirements.
Highlights
- Greenfield, but with real constraints. You're building on Azure/AWS with enterprise security requirements. The challenge is designing deployment and observability for LLM-backed services. You need to track output quality, cost per invocation, and model drift.
- Enterprise complexity, startup autonomy. Ownership and greenfield environment of a startup, with the integration challenges of a Fortune 200: connecting AI services to real enterprise systems.
- More than infrastructure. Your core is SRE, but you'll also write agent code in TypeScript and Python, work with data pipelines, and ship features alongside the team.
What the Work Looks Like
AI Service Infrastructure - Design and maintain deployment and release infrastructure for AI agents. The stack is cloud-native (Azure/AWS), with services that call LLM APIs, connect to enterprise systems, and handle structured data.
Observability & Reliability - Build monitoring and observability for AI services. Ensure model response quality doesn't degrade silently by tracking errors, logging cost spikes, and monitoring upstream API changes.
Security & Compliance - These agents handle sensitive workflows with elevated security requirements. You will work with our company's security team on standards, but you own how they're implemented in the infrastructure.
Developer Experience - Create tooling that makes it easy for the team to build, test, and deploy. The patterns you set become the team's defaults.

We're looking for an AI and Automation Engineer to join our Automation team and help build the internal tools, AI agents and automation systems that power how we operate.
This role combines hands-on engineering with impactful product development. The work is split between writing code (TypeScript, React, Python) and designing and implementing automation workflows using low-code platforms.
You'll take part in building intuitive internal web applications that teams enjoy using, developing AI-driven solutions that streamline repetitive processes, creating insightful dashboards to support decision-making, and integrating systems that help the business run smoothly and efficiently.
You'll work alongside our Tech Lead and a US-based IT Automation Engineer, contributing across the full spectrum from designing React-based internal tools to building RAG pipelines to orchestrating multi-step business workflows.
What You'll Do
Design and build internal web applications using TypeScript and React that serve teams across the organization.
Create intuitive interfaces that make AI capabilities and automation outputs accessible to non-technical users.
Build and maintain RAG pipelines - including document processing, embedding, vector storage, retrieval, and evaluation.
Work with LLM APIs (Claude API, OpenAI API, AWS Bedrock, Vertex) and implement prompt engineering patterns (tool/function calling, structured outputs, few-shot) with proBuild connectors, APIs, and data flows that keep systems in sync and processes running smoothly.
Work with data from across the business to support decision-making.
Design and maintain automation workflows using low-code/no-code platforms (Workato).
Integrate AI solutions into core business tools - Slack, Jira, Salesforce etc.

we are looking for a talented Senior Software Engineer
The team is responsible for processing structure and unstructured medical data from multiple external sources while building and maintaining an internal serving platform. Our key challenges include operating at scale, integrating with diverse external interfaces, and ensuring the data is served in a consistent and reliable manner.
Responsibilities:
Lead development processes from ideation to production
Collaborate with product, medical, and software teams across the organization.
Own the design and evolution of the data ingestion and serving platform.
Mentor and guide junior and mid-level engineers.
Define best practices for system reliability, scalability, and observability.
Lead technical decisions around distributed systems, APIs, and integrations.
Build a customer-centric product with a deep understanding of the complex healthcare industry