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we are seeking a Junior Cybersecurity Architect (GRC & Risk) to support governance, risk analysis, and security process design. The role focuses on translating security findings into structured mitigation plans and improving methodologies and frameworks-without hands‑on technical configuration.You will work with CISOs, security leaders, engineering teams, and customers on due diligence, maturity assessments, and development of security processes and documentation.

Responsibilities
Conduct customer and third‑party security assessments and questionnaires.
Lead or support mitigation workshops and build actionable remediation plans.
Develop and refine methodologies, processes, and architectural guidelines.
Map technical findings to governance, risk, and control gaps.
Perform NIST CSF 2.0-aligned maturity assessments.
Produce clear reports and executive summaries.
Maintain internal documentation and ensure framework alignment.

This position is intended for a candidate with a background in security engineering who is looking to transition into a cybersecurity architecture role. The role focuses on reviewing cloud and SaaS environments, assessing the effectiveness of security controls, and supporting security maturity assessments and mitigation planning activities.This is a junior‑level architecture role with an emphasis on technical analysis, control review, and security design assessment. The position prioritizes architectural evaluation and advisory activities over hands‑on implementation.

Responsibilities
Perform security maturity assessments, including reviews of technical controls, configurations, and architectural designs, aligned with the NIST CSF 2.0 cybersecurity framework.
Conduct technical configuration and control reviews of cloud environments and SaaS platforms (read‑only / observer role).
Analyze security architectures and technical implementations to identify gaps, risks, and improvement opportunities.
Translate technical findings into clear architectural observations and recommendations.
Produce structured assessment reports and technical findings for both technical and non‑technical audiences.
Maintain internal technical documentation and contribute to architectural knowledge within the team.
Collaborate with R&D and product teams on ad‑hoc cases as a cybersecurity technical subject‑matter contributor.

A new type of finance role designed for an AI-driven organization. You will combine strong FP&A fundamentals with curiosity for GenAI tools, modern analytics, and SaaS monetization. Working closely with AI leaders, product teams, and business stakeholders, you will help translate innovation into financial insights while contributing to core financial execution.

What will your job look like?
Support planning, forecasting, and performance analysis for Data & GenAI initiatives
Build financial models for AI solutions, SaaS offerings, and data-driven business cases
Analyze monetization approaches for GenAI-driven capabilities and internal transformation programs
Design and track KPIs measuring efficiency, productivity, and value from AI adoption
Partner closely with product, engineering, and AI leaders to translate roadmaps into financial narratives
Use GenAI and analytics tools to streamline reporting and improve decision-making workflows
Maintain ownership of core FP&A deliverables while supporting strategic decision-making

Financial planning and analysis to ensure accurate recording and enable decision-making, measurements, budget control and ongoing monitoring.

What will your job look like?
Collecting data from all relevant partners and reflect financial data in the system and analyze financial data, perform multiple scenarios, build models and identify trends
Extract major insights and conclusions from the analysis
Provide relevant key partners with main takeaways and recommendation
Supporting the business in decision making

Lead a large-scale engineering organization in the Data & AI domain, define the technological strategy, manage global multiple teams and managers, and drive the delivery and innovation of advanced AI-powered solutions and data platforms.

What will your job look like?
Lead a multi-disciplinary engineering group including software engineers, data engineers, ML engineers, and team managers, while shaping the long-term technological and product roadmap.
Define the Data & AI strategy for the product, including architecture, scalability, engineering standards, and best practices.
Oversee end-to-end development of Data and AI capabilities, including model integration (LLMs/ML), data pipelines, analytics components, and production-grade AI services.
Work closely with Product, Architecture, Delivery, and customer stakeholders to translate business needs into scalable AI and data-driven solutions. Manage agile engineering processes: planning, prioritization, execution, technical design reviews, DevOps practices, and quality control.
Lead innovation initiatives in Generative AI, evaluate emerging technologies, and own POCs, pilots, and transformation activities.
Manage budgets, recruitment, talent development, leadership growth, and organizational KPIs.
Represent the Data & AI domain in executive forums, customer discussions, and cross-organizational strategic initiatives.

Financial planning and analysis to ensure accurate recording and enable decision-making, measurements, budget control and ongoing monitoring.

What will your job look like?
Collecting data from all relevant partners and reflect financial data in the system and analyze financial data, perform multiple scenarios, build models and identify trends
Extract major insights and conclusions from the analysis
Provide relevant key partners with main takeaways and recommendation
Supporting the business in decision making

We are seeking a highly skilled and visionary Lead Data Scientist with deep expertise in Generative AI to lead high-impact initiatives at the frontier of AI innovation. This role requires a unique blend of advanced technical skills, domain specialization, leadership ability, and a passion for delivering real-world impact. You will guide a small team of talented data scientists and work collaboratively across engineering and product teams to design, build, and deploy intelligent, domain-specific multi-agent systems.

What will your job look like?
Lead the design of complex, domain-specialized multi-agent Generative AI systems.
Provide technical mentorship and leadership to a team of 3-4 data scientists.
Drive hands-on research and rapid prototyping in areas including LLM fine-tuning, prompt engineering, agentic workflows, and self-improving systems.
Collaborate with product managers, engineers, and domain experts to identify opportunities and deliver AI-driven features and products.
Evaluate and integrate state-of-the-art models and tools from the GenAI ecosystem, including open-source and proprietary solutions.
Translate research outcomes into actionable product features and influence AI strategy and roadmap.
Maintain high standards for scientific rigor and data integrity throughout the development lifecycle.

Financial planning and analysis to ensure accurate recording and enable decision-making, measurements, budget control and ongoing monitoring.

What will your job look like?
Collecting data from all relevant partners and reflect financial data in the system and analyze financial data, perform multiple scenarios, build models and identify trends
Extract major insights and conclusions from the analysis
Provide relevant key partners with main takeaways and recommendation
Supporting the business in decision making

Financial planning and analysis to ensure accurate recording and enable decision-making, measurements, budget control and ongoing monitoring.

What will your job look like?
Collecting data from all relevant partners and reflect financial data in the system and analyze financial data, perform multiple scenarios, build models and identify trends
Extract major insights and conclusions from the analysis
Provide relevant key partners with main takeaways and recommendation
Supporting the business in decision making

Responsible for revenue recognition accounting and related areas.

What will your job look like?
Lead the quarterly close process to ensure accurate revenue recognition and in-depth analysis of all revenue-related accounts in the Companys financial statements.
Prepare and present quarterly revenue analysis and insights to senior management.
Take full ownership of revenue-related matters in front of external auditors, ensuring full compliance with applicable accounting standards.
Guide and educate the Finance organization on revenue-related accounting policies, best practices, and processes.
Partner closely with Finance business teams and Amdocs business units, overseeing and advising on new and potential customer deals from a revenue recognition perspective.

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.