דרושים » תוכנה » AI & Data Financial Analyst

We are looking for an AI & Automation Engineer to design, build, and enable enterprise AI infrastructure and automation solutions.
This role focuses on AI architecture, workflow automation across IT and business applications, and monitoring, governance, and cost management of AI tools and agents.
You will work at the intersection of AI platforms, IT operations, and business automation, enabling scalable, secure, and cost-effective AI adoption across the organization.
Responsibilities:
Select and integrate AI tools, frameworks, and platforms aligned with enterprise IT standards.
Ensure scalability, security, reliability, and compliance of AI infrastructure.
Enable AI solutions from concept to production, including:
AI-powered IT tools
AI agents and copilots
AI services integrated into business applications
Collaborate with IT, DevOps, Security, and Business teams to deploy AI solutions smoothly.
Build reusable AI enablement patterns, templates, and best practices.
Automation of Workflows
Design and implement automation of IT and business workflows using AI and orchestration tools.
Integrate AI agents into:
IT operations (ITSM, monitoring, incident response)
Business applications and internal systems
Improve efficiency, reliability, and user experience through intelligent automation.
AI Monitoring, Usage & Financial Governance
Define and implement monitoring for AI systems, including:
Usage tracking
Performance and reliability
Model and agent behavior
Track and analyze financial usage and cost of AI tools, APIs, and platforms.
Establish governance frameworks for responsible and controlled AI usage.

You will participate in implementing a new strategic platform offering Generative AI (Gen AI) capabilities such as inference, fine-tuning, data curation, data labeling, and more.

We are seeking a highly skilled Gen AI software engineer to design, develop, and deploy state-of-the-art, scalable, efficient Gen AI solutions. You will be part of a high-performing engineering team that values collaboration, innovation, and teamwork. This role is perfect for someone who thrives in an environment where ideas are shared, challenges are met together, and success is a collective achievement.

Responsibilities:
Designed and implemented Gen AI platform components using Python and modern microservices.
Drive engineering and operational excellence and best practices.
Collaborate with tech, product, program, and business peers to deliver customer value and drive product vision.
Drive the end-to-end development of AI systems, from research and experimentation to deployment and scaling.
Mentor and support engineers, fostering a culture of collaboration, knowledge-sharing, and continuous learning.
Analyze complex problems and identify and define the requirements to solve them.
Apply DevOps principles to maintain high-performance and scalable AI systems.
Design and implement secure APIs, ensuring data protection and safe interaction with AI models.
Stay updated on the latest Gen AI trends and technologies, bringing fresh ideas to the team.

We are looking for an experienced Cloud Data Presales professional who helps customers understand the possibilities of big data, analytics, AI, and ML across EMEA. As a Data Presales, you will be the first point of contact for the customer regarding data, and you will be responsible for defining the right data strategy for them. As a Data Presales, you will work closely with Data Architects, Engineers, and Project Managers. Perform feasibility analyses, present data use cases, simplify and hold presentations in front of IT and non-IT people, and position the topic of data and AI with customers.

Responsibilities:
Support the Sales team by explaining opportunities in Big Data, Analytics, AI, and ML.
Guide clients to understand data: opportunities, threats, and action plans.
Conduct interviews, brainstorming sessions, and workshops with client teams and executives on data-related topics and projects.
Develop strategic and action plans.
Collaborate with external vendors and partner technologies.
Comprehensive project and team management of Data Scientists, Engineers, and other stakeholders.
Be an online and offline ambassador for the data practice.

a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.

What You'll Do
Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives
Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores.
Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security
Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization
Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
Enhance the team's dev-ops capabilities.

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.

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.

Lead and mentor a team of software engineers developing Sensing AI SDK. Architect and implement high-performance sensing SW components for AI, vision, Audio and voice optimized for vectorize SIMD execution. Collaborate with compiler and DevOps teams to ensure efficient development and deployment. Drive technical excellence through code reviews, design discussions, and continuous improvement. Own the SDK roadmap, planning, and delivery cycles. Engage with customers to enable successful pre-sale processes, support integration and gather feedback.