דרושים » הנדסה » Head of data AI

We are seeking a visionary AI Product Manager to orchestrate the convergence of our diverse AI stack into a cohesive, real-time product.

You will not just manage a feature; you will own the fusion of these technologies. From Generative Video models that render lifelike avatars, to Speech AI engines (ASR/TTS) that handle nuanced voice interaction, to the LLM & RAG layers that provide the brain and context-you will lead the strategy that turns these individual components into a unified, low-latency Face-to-Face conversational engine for the enterprise.



The day-to-day

Strategic Collaboration: Partner closely with the Head of AI and Head of Product to align the generative media roadmap with technical constraints.
Orchestrate the Multi-Model Stack: Define the product vision for a complex architecture-integrating Latent Diffusion for visuals, Transformer-based Speech AI, and LLMs-into a seamless real-time loop optimized for minimal Time-to-First-Token (TTFT).
Advance Video Generation Tech: Spearhead the deployment of diffusion-based video synthesis and neural rendering.
Establish Benchmarks: Set standards for temporal consistency, high-fidelity lip-sync, and dynamic avatar behaviors that meet enterprise bitrate standards.
Optimize the Brain (LLM & RAG): Lead the strategy for our cognitive layer, overseeing Vector Database selection and embedding models for RAG pipelines.
Ensure Accuracy: Ground AI responses in enterprise data, strictly minimizing hallucination rates and optimizing context window usage.

the corporate genai lead drives accelerates and scales genai adoption across our company to deliver measurable business impact.
this role translates emerging ai capabilities into structured, secure and business driven, working cross-functionally with r&d, it, Cyber security, and corporate teams, leading vendor relations and evaluating new ai solutions.
the genai director will operate at the intersection of technology strategy and execution - aligning priorities, enabling use cases, and shaping the genai roadmap to support our sustainable growth. what will your job look like: identify and prioritize high-impact genai use cases across engineering and corporate functions, aligning initiatives with measurable business value
lead cross-functional initiatives from concept through pilot and scalable deployment, ensuring clear ownership and delivery milestones
define and evolve the genai platform and infrastructure roadmap to support secure, scalable, and cost-efficient adoption
partner with it, Cyber security, and engineering teams to ensure secure and compliant implementation.
evaluate external tools, lead the adoption lifecycle from poc to enterprise rollout, and drive data -driven build-or-buy decisions
track adoption, business impact, kpis, and roi across the genai portfolio, adjusting priorities as needed
lead the genai internal community, strengthen internal knowledge sharing, and ai standards responsibilities.

This role is designed for individuals who are not only technically proficient but also deeply passionate about pushing the boundaries of AI and machine learning through innovative engineering and collaborative research.

Key Responsibilities
Profile and optimize the training process to ensure efficiency and effectiveness, including optimizing multimodal data pipelines and data storage methods.
Develop high-performance TPU/GPU/CPU kernels and integrate advanced techniques into our training framework to maximize hardware efficiency.
Utilize knowledge of hardware features to make aggressive optimizations and advise on hardware/software co-designs.
Collaboratively develop model architectures with researchers that facilitate efficient training and inference.
Design, maintain, and evolve a high-quality, shared codebase that emphasizes correctness, readability, extensibility, testing, and long-term maintainability, while balancing performance requirements.

This role focuses on pioneering model architecture and pre-training algorithms, shaping the next generation of our foundational generative AI models.

What you will be doing
Pre-train and fine-tune video, audio, and image generative models to pursue state-of-the-art results.
Publish papers and open source models to benefit the research community and advance the field.
Design and implement machine learning models for text-to-audio and text-to-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficient training and inference.
Build new controls and capabilities into generative text-to-audio and text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the fields of image, video, and audio.
Work closely with product teams to integrate AI models into applications and services.
Conduct experiments and prototype new concepts to advance the capabilities of our AI tools.

we're building the financial infrastructure that powers global innovation. With our cutting-edge suite of Embedded payments, cards, and lending solutions, we enable millions of businesses and consumers to transact seamlessly and securely. With 900+ employees worldwide and an R&D center of over 160 employees in Jerusalem - were reshaping how financial technology is developed and delivered..
The Role:
As AI capabilities accelerate across the bank, we need an engineer to design and enforce safe AI usage-protecting customer data, preserving model integrity, and meeting our regulatory obligations. You'll be the architect of guardrails, tooling, and policies that make AI both secure and useful for product and internal teams. This isn't about slowing things down; it's about building the trust layer that lets innovation move fast without breaking things.
Who You Are:
You're a security engineer who's excited about the AI wave-someone who sees GenAI and LLMs as fascinating puzzles to secure, not just threats to mitigate. You've spent 5+ years in Security Engineering, AppSec, or Cloud Security, and at least 1-2 of those years have been spent getting your hands dirty with AI/ML or data -intensive systems. You're equally comfortable dissecting a prompt injection attack as you are writing a Terraform module or shipping a Python library. You know your way around AWS and/or Azure, modern app stacks ( Python /TypeScript, REST/gRPC, containers/Kubernetes), and can translate security requirements into Developer -friendly tooling-not just PDF policies that gather dust. You communicate clearly in English and Hebrew, thrive in regulated environments, and understand that security in financial services means mapping controls to frameworks like FFIEC, SOC 2, and PCI DSS-and actually having the evidence to prove it.
What Youll Actually Be Doing:

* Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
* Implement data minimization controls for GenAI/RAG workloads: context filtering, leastprivileged retrieval, document-level ACL enforcement, vector store hardening, and secure token/secret handling.
* Threat model AI systems (apps, agents, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/jailbreaks/ data exfiltration) and build mitigations.
* Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive- data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
* Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
* Evaluate thirdparty AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
* Partner across Security, data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
* Lead/participate in AI redteaming: automated jailbreak/promptinjection tests, safety benchmarks, purpleteam exercises, and response playbooks for AI incidents.
* Enable the org with concise guidelines, examples, and training on safe AI development and usage.

Why Youll Love Working Here:

* Flexible hybrid work model: three days a week at our Jerusalem office
* Monthly wellness reimbursement - from therapy to gel manicure, it's up to you
* Full Keren Hishtalmut, private health and dental insurance
* Volunteer days, donation matching, Yoga and Pilates
* A supportive, collaborative culture that puts our people first
Next Step:
Hit Apply!

We are looking for a hands-on professional who will take ownership of customer-facing AI solutions, become a central point of contact for key customers, and work closely with our product and AI development efforts.

This is a cross-functional role with real impact on how the company operates and grows over the coming years.

Responsibilities

Own and manage ongoing relationships with customers, gradually taking on a central Customer Success role
Analyze complex business needs and translate them into CRM and AI-based solutions
Define and design AI agents, automated processes, and advanced workflows
Lead and support solution implementation with customers, including hands-on involvement when needed
Work closely with development and implementation teams
Identify problems, propose solutions, and take full ownership from definition through execution
Continuously improve internal workflows and delivery processes using AI