לוח משרות דרושים הייטק AI  בתל אביב יפו, לחיפוש זה נמצאו 174 משרות

In Customer Care and Trust & Safety, real people are on the other side of every decision. You're the reason why our users feel safe using our company, and you take that seriously. From quality assurance specialists to fraud analysts, those we're looking for are stakeholder-savvy and treat every case like it's the only one that matters. So if you're methodical when the details affect peoples livelihoods, we want to hear from you.
Join our dynamic Customer Care team as a Chatbot Project Lead, taking the reins on our chatbot roadmap and stakeholder communication. This is a critical role stepping in to guide a talented team, ensuring seamless project delivery and strategic alignment as we enhance our AI-powered customer solutions.
What am I going to do?
Manage the end-to-end chatbot roadmap and sprint delivery, ensuring all project deadlines and key performance indicators are met with precision.
Translate overarching company strategic goals into actionable chatbot experience improvements, effectively communicating updates and insights to diverse stakeholders.
Mentor and provide hands-on guidance to team members, fostering their growth in areas like advanced prompting techniques on platforms such as Forethought.
Leverage data analysis to deeply understand chatbot performance, driving continuous optimization and informing strategic decision-making.
Facilitate key team meetings and foster a collaborative and inclusive team culture.

We are hiring a hands-on AI expert to shape our intelligent platform, organizing complex real estate data into actionable insights and predictive models that power smarter investment decisions.

Responsibilities

AI/ML Architecture: Design and implement scalable AI systems using models such as
LLMs (e.g., OpenAI, Anthropic) and computer vision (e.g., YOLO, CLIP)
MCP Integration: Architect and orchestrate model context flows using MCP or similar
frameworks to deliver personalized, context-aware experiences
FinTech Platform Integration: Embed intelligent features into our backend and frontend
systems, ensuring seamless UX and robust performance
Hands-On Development: Write production-grade code across Python, TypeScript, and
Node.js. Own key modules and guide technical decisions
Team Leadership: Mentor a few developers, set engineering standards, and foster a
culture of experimentation and excellence
Data Strategy: Collaborate with product and data teams to define training datasets,
feedback loops, and model evaluation pipelines

we are looking for a AI Algorithm Tech Lead.
This is a role in core AI group, which specializes in developing cutting-edge AI solutions in healthcare, enhancing medical imaging and diagnostics. As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities:
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

we are looking for a AI Software Engineer.
This is a AI Software Engineer role within AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.
Responsibilities:
Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
Develop and maintain high-quality, scalable, and efficient code.
Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems)

we are looking for a Director of GenAI Operations.
The Director of GenAI Operations is responsible for driving the adoption, maintaining standards, and ensuring the effective use of AI across . This role partners with business and technical stakeholders to identify high-impact opportunities, translate them into scalable AI-enabled workflows, and ensure responsible implementation aligned with company priorities and producing measurable ROI.
This role combines strategy, execution, enablement, and governance. Director of GenAI Operations will define standards, build repeatable playbooks, support cross-functional adoption, and help employees and teams use AI tools in a practical, measurable, and secure way.
Main roles and responsibilities:
Partner with business leaders to identify, assess, and prioritize AI and automation opportunities across workflows and processes.
Hands-on creation of scalable AI-enabled workflows and operating models that align with business needs, available tooling, and business systems.
Translate use cases into clear implementation requirements, process definitions, documentation, and success criteria.
Build and maintain AI playbooks, standards, usage guidelines, and best practices for employees and teams.
Lead enablement activities, including onboarding, workshops, training materials, office hours, and internal knowledge sharing.
Drive adoption of approved AI tools and capabilities across the organization, helping teams move from experimentation to sustainable usage.
Collaborate with business stakeholders to ensure AI usage aligns with governance, privacy, security, confidentiality, and compliance requirements.
Establish feedback loops, reporting, and measurable KPIs for AI adoption, productivity gains, and business outcomes.
Monitor external AI trends, vendor capabilities, and emerging practices, and recommend improvements relevant .
Support vendor evaluation, tool rationalization, and the rollout of new AI capabilities where needed.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

We are seeking a talented and experienced GenAi Enigneer to build AI powered applications that involve various technology stacks and data on top of the platform.

We are looking for a GenAI & Competitive Intelligence Engineer to join our Competitive Intelligence team. This role combines deep technical expertise with a builder's mindset to design, implement, and maintain advanced AI-powered systems for automating knowledge collection, generating competitive insights, and ensuring broad internal knowledge sharing across the organization. You will spearhead AI solution projects from initial concept through execution and widespread adoption.

As a GenAI & Competitive Intelligence Engineer , you will
Main role: Build, implement, and maintain the AI-powered intelligence stack, using LLMs, agentic capabilities, MCPs, Skills, and advanced RAG, to automate data collection, analysis and sharing
Make knowledge impossible to miss inside . Build the competitive intel teams interfaces that get the right competitive insight to the right stakeholder at the right time
Drive projects from concept to execution to delivery
Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness
Ensure the scalability and reliability of LLM-based system architectures
Engage with requirement gathering and product discussions with internal customers
Be the focal point for collaborating with IS, IT and data science teams
Have solid understanding of various aspects of the software development supply chain, including DevOps, DevSecOps and MLOps, and conduct in-depth technical research around them

We're looking for a Senior AI Product Manager to take ownership of core areas of our B2B platform - the point where powerful AI capabilities become real products that customers rely on. We've already built the foundation: rich data, agentic infrastructure, and deep domain intelligence. Now we need someone who can take what's working with one customer and make it work everywhere - productizing capabilities, scaling them across our customer base, and raising the quality bar as they grow.

This is a hands-on builder role. You'll work in close, direct partnership with both customers and R&D - running discovery, analyzing the data, and prototyping ideas yourself, then teaming up with R&D to bring them to life at scale.

This is a fast-moving area, and we'll shape the exact scope together, based on where you can create the most leverage for the business. We're looking for true startup reflexes: the ability to shift focus as priorities shift, zero in on what matters most this quarter, and make clear, deliberate trade-offs.

If you thrive in a fast-paced startup environment and want to build AI products that make complex insights accessible and actionable for a real-world, >$1B industry, this role is for you.

What You'll Do

Own core areas end to end - strategy, discovery, execution, and measurement. Define what success looks like in numbers, and stay accountable to it well beyond launch.
Productize and scale what works. Turn capabilities proven with one customer into products that work seamlessly across your entire customer base.
Lead discovery yourself. Run customer and prospect conversations to uncover what people will actually pay for, and bring back a scoped, evidenced bet.
Prototype your ideas. Go from concept to working prototype using coding agents and AI tooling, with a design bar high enough to serve as a real proposal.
Own quality. Define what "good" means for our agents, build the evals to measure it, and raise the bar on reliability, cost, and trust as the system evolves.
Partner deeply with R&D. Engage on technical trade-offs - accuracy, latency, cost, build vs. buy - and earn the team's respect through substance.
Drive it to market. Team up with design, sales, marketing, and customer success to package, position, and launch it, then feed adoption data back into the roadmap.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.

What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our company core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements
Design and oversee API strategies, event-driven architectures, and middleware patterns that support scalable AI feature delivery - including agentic workflows, intelligent data transformation, anomaly detection, and natural language interfaces layered onto ERP and CRM data
Collaborate with Engineering during build phases, conducting architecture reviews, providing hands-on guidance, and resolving complex technical blockers
Define non-functional requirements - latency, security, auditability, model drift monitoring - for AI components embedded in mission-critical business processes
Establish MLOps and LLMOps practices appropriate for our enterprise environment: model versioning, observability, and rollback procedures for production AI workloads

Were hiring a Senior AI Analyst to join our Research team and help shape our AI-driven cybersecurity platform. In this role, youll dig deep into how our AI agents perform, uncover whats working and where the opportunities are, and turn that analysis into insights that shape the roadmap, strengthen the product, and drive customer value and growth.

We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv.
This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company.
What Youll Do:
Design and build reusable AI platform capabilities used across multiple products.
Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities.
Design and build internal AI platforms such as organizational knowledge (Brain), AI developer tools, autonomous engineering workflows, and shared AI services.
Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform.
Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities.
Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment.
Build and operate production AI services using modern cloud-native technologies.
Improve the reliability, scalability and observability of AI systems.
Define engineering standards, reusable patterns and best practices for AI development across engineering teams.
Lead technical proof-of-concepts and drive adoption of innovative AI technologies.
Mentor engineers and provide technical leadership on complex AI initiatives.

A full-time Applied AI Engineer role focused on building and optimizing our LLM-powered clinical compliance engine. You will design, implement, and refine AI systems that analyze clinical documentation, detect compliance issues, and generate actionable insights for healthcare providers.
Key Responsibilities
Design and implement LLM-based rule engines for clinical compliance detection
Build RAG systems and semantic search pipelines for clinical documentation
Optimize prompts, fine-tune models, and evaluate AI system performance
Collaborate with clinical experts to translate regulatory requirements into AI workflows
Monitor and improve AI accuracy, latency, and cost efficiency in production
Develop evaluation frameworks and testing strategies for AI outputs.