לוח משרות דרושים הייטק AI , לחיפוש זה נמצאו 267 משרות

Required Senior AI Product Manager - Sales Intelligence
The Most Interesting Corner:
We reveal everything that happens online. But in the Sales Intelligence (SI) department, we dont just show data-we make it act.
Think of SI as a high-growth startup embedded within a data giant. We sit on top of one of the world's most sophisticated datasets, but we operate with the speed, agility, and "build-it-ourselves" mentality of a day-one venture. We aren't just building another B2B dashboard; we are redefining the "B2C-style" experience for the modern seller.
Why this role is a game-changer:
Most sales tools are built for managers and "Ops" (the backbone). This role is for the Salesperson. Your mission is to build the "Superpower Suite" for Sales Persons, SDRs, Account Executives, and CSMs. We are on a crusade to delete the admin work that every salesperson hates. If a task is "boring," "manual," or "admin-heavy," your job is to build an AI product that does it for them-so they can get back to what they love: winning deals.
How we build with AI:
We don't just talk about AI; we live in it. The SI department is a playground for builders.
The Stack: We are deeply embedded with tools like Claude, Cursor, and AI-driven code/design workflows.
Rapid Prototyping: We build our own prototypes and products in-house, collaborating tightly with a world-class R&D team that moves at lightning speed.
Agentic Future: We are moving beyond simple automation. You will define the strategy for AI Agents and AI Skills-autonomous systems that can research prospects, handle "boring" outreach, and deliver real-time "what to say next" cues during live calls.
A day in the life...
Hustle Research: Deep-dive with Sales and CSM teams to find the friction. If theyre spending 2 hours a day on "manual research," youre there to turn that 2 hours into 2 seconds.
B2C Mindset in B2B: Design tools that are as addictive and intuitive as your favorite consumer apps. If its not a joy to use, its not finished.
AI Orchestration: Lead the charge on Agentic Workflows. Youll define how AI "skills" (like predictive lead scoring or automated prospect discovery) fit into a seamless seller journey.
Cross-functional "Startup" Mode: Partner with data scientists to turn complex signals into simple "buying cues" while acting as the bridge between "what's possible" and "what's usable."

abra professional services is seeking for an AI Engineer (GenAI & Integration) The AI Engineer (GenAI & Integration) designs, builds, and deploys AI-powered solutions within enterprise systems and business workflows. The role focuses on practical application of AI by integrating models, data, and tools into real operational environments to enable automation, decision support, and productivity gains. The role emphasizes implementation and integration rather than model development, bridging AI capabilities with enterprise systems and workflows. Key Responsibilities
* Design and implement end-to-end AI solutions aligned with business needs
* Integrate AI capabilities with enterprise systems, APIs, and data platforms, including legacy environments
* Develop AI agents and automation workflows for multi-step task execution
* Build AI-driven applications, including copilots and decision-support tools
* Develop and maintain integration layers, including MCP-based and similar AI integration services
* Evaluate, test, and validate AI outputs to ensure accuracy, reliability, and quality in production
* Deploy, monitor, and optimize AI solutions in production environments
* Maintain clear and structured documentation across solutions, integrations, and processes
* Lead implementation of AI solutions in collaboration with business, IT, and engineering teams to ensure scalable and compliant delivery

we are building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
we are an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.
Qualifications
Your Impact
Design and implement automated evaluation loops, static analysis, and rigorous quality gates to ensure the ADLC process doesn't just write code, but consistently produces great, production-ready code.
Help the team tackle complex, hard problems to elevate our autonomous development product from "good" to "excellent".
Lead complex initiatives in Context Engineering and Prompt Engineering.
Manage and orchestrate the complex ecosystem of autonomous agents utilized for internal development.
Serve as a leading individual in a very strong team professionally and personally - Were looking for someone who not only delivers his own work but improves that of those around them.
Find space for growth to push the entire team or group forward - New projects, changing processes or improving existing tools.
View prompt engineering as a core engineering discipline-where rewriting agent behavior is a versioned, reviewed, and tested code change.
Act with a debugging temperament; conduct deep-dive analyses of raw agent transcripts to diagnose non-deterministic failures and ascertain root causes instead of merely working around them.

This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production - owning outcomes end-to-end, including deployment, monitoring, cost, and business impact.

We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI.

What You Will Build
AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role - not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space.
Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requests as a risk to momentum. Use feature flags, canary releases, and rollback architecture to manage risk through isolation - not through avoidance.
AI-Augmented Engineering Workflow. Leverage AI-assisted development tooling (code generation, automated testing, architecture prototyping) as a core workflow multiplier. Evaluate and experiment with emerging AI tools and frameworks with direct hands-on engagement. Bring technical depth to AI fluency - architecture and capability tradeoffs, not surface-level awareness.
End-to-End Ownership. Own your work from design through production deployment, operational monitoring, and business impact measurement. Accountability extends beyond the feature to CI/CD pipeline health, observability, cost efficiency, and domain-level outcomes.
Architectural Decision-Making. Make pragmatic, timely architectural choices that balance modern AI and data technologies with reliability, cost, and delivery speed. Distinguish reversible vs. irreversible decisions and move forward without waiting for consensus on the former. Document decisions in lightweight ADRs and own the outcomes.
Cross-Functional Collaboration. Partner with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions. Operate with business awareness - understand how your systems impact revenue, customer outcomes, and strategic priorities.

We're looking for a driven, experienced, and forward-thinking Product Operations specialist to join our Product organization and help drive operational excellence across our product lifecycle. This is a high-impact role where you'll work with cross-functional teams and play a key part in shaping the future of OX by streamlining processes and scaling our capabilities.

What You'll Be Doing
Lead or support the optimization of internal workflows, aligning and automating processes across the Product and R&D organizations- leveraging people or AI.
Collaborate with cross-functional stakeholders to define, implement, and track key product success metrics and data-driven insights.
Drive efficiency by identifying bottlenecks, repetitive tasks, and inefficiencies across the product lifecycle - and fixing them by establishing best practices for cross-team collaboration.
Spearhead the integration and adoption of advanced AI tools, ensuring the product team is equipped with the best infrastructure to succeed.
Help us continuously improve by fostering a culture of agility, data transparency, and collaborative effort across the entire organization.

We are seeking an Senior AI Engineer to design, build, and deploy AI-powered capabilities within our product.

This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.

The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure. transforming AI technologies into practical applications.

Responsibilities:
Build applications powered by machine learning and large language models (LLMs).
Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.
Integrate AI functionality into backend services and product workflows.
Design and implement retrieval pipelines, embedding pipelines, and inference workflows.
Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.
Create scalable AI architectures capable of handling production workloads.
Package and deploy AI models as production services.
Optimize inference performance, scalability, and latency.
Monitor AI services to ensure reliability and performance.
Develop backend services and APIs that expose AI capabilities.
Integrate AI systems with databases, internal services, and external APIs.
Contribute to system architecture and microservices design.
Implement logging, metrics, and observability for AI systems.
Track model performance and system reliability in production environments.
Work closely with product managers, engineers, and data scientists.

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 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

Were looking for an execution-focused Product Manager to own initiatives end-to-end within a complex B2B SaaS platform.
The role combines product thinking with hands-on execution: from writing requirements and aligning teams, to prototyping and occasionally shipping changes directly to production using AI-assisted tools.
This role is designed for people who want responsibility, speed, and the ability to build, not just plan.
What Youll Do
Own product initiatives from kickoff through post-release.
Translate customer and internal input into clear, actionable product requirements.
Align engineering, design, and stakeholders on scope, tradeoffs, implementation details and delivery decisions.
Own feature rollout, enablement, and activation with CS.
Build deep understanding of customer personas, use cases, and desired outcomes by running direct customer conversations, joining onboarding and support sessions.
Take hands-on ownership of features post-launch, becoming the internal product SME through customer adoption and successful use cases.
Build & ship smaller product changes directly when needed using Cursor and AI-assisted tools

We're looking for a Senior AI Infrastructure Engineer to join a group that specializes in Security and Networking, and specifically ML/AI, MLOps, and agentic AI development. As a Senior AI Infrastructure Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, and security architects to ensure smooth development, deployment, evaluation, and optimization of AI pipelines, models, and agents. This role requires a balance of high-level engineering rigor and a collaborative spirit; youll be a technical anchor and a supportive peer for teams across the organization.



What youll be doing:

Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production.

Managing ML/agentic workflows to ensure performance, high availability, resource efficiency, and cost-effectiveness.

Designing and implementing pipelines and frameworks for AI training, inference, and experimentation.

Partnering with data scientists and security architects to operationalize AI agents, including packaging and integration with existing systems. This includes contributing to and reviewing code, design documents, and test plans.

Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes, ensuring reliable deployments and rollbacks.

Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production.

Implementing access controls, authentication mechanisms, and encryption standards to keep our AI models and data secure.

Documenting guidelines and leading knowledge-sharing sessions to elevate the teams collective development expertise.

Our work in Networking and AI is transforming the world's largest industries and profoundly impacting society. Our Networking product security team is looking for an outstanding technical AI red teamer with hands-on safety and security experience to help us improve the safety posture of AI models, systems and infrastructure. In this role you will reduce risk, threats, and vulnerabilities in our networking AI products.

What you'll be doing:
Drive hands-on safety and security research on a range of AI and networking products.
Develop tools and processes to expose novel weaknesses in AI models and systems to preempt threats.
Participate in defining and ensuring AI development processes meet safety and security standards.
Partner with cross-functional teams to understand needs and implement solutions.
Be a technical focal point across multiple teams and provide hands-on AI safety, security and engineering expertise.

We are seeking a Senior AI Engineer to join a talented and fast-moving AI Engineering team. We're the central hub for AI across, driving innovation and putting AI to work for every team and product in the company.
AI already plays a foundational role in how we operate. It lets us ship features quickly and at scale, equips non-technical team members with tools that boost their productivity, and underpins much of the innovation happening across the company today.
If this kind of environment excites you - and if you believe great engineering means crafting the most effective and elegant solution within real-world constraints - we'd love to hear from you.
What You'll Be Doing:
Design, build, and maintain reusable AI capabilities - spanning models, tools, APIs, and platforms that support both internal operations and customer-facing products.
Develop and maintain our internal MCP server, giving AI agents easy and secure access to our extensive data stores.
Create and implement rigorous evaluation frameworks and AI guardrails to protect our value and ensure model reliability.
Cultivate deep expertise and establish sustainable AI engineering practices across the organization.
Champion AI readiness and track adoption company-wide to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Own projects end to end - from gathering requirements from non-technical stakeholders through development, deployment, and ongoing operation.
Serve as a consultant and advocate for AI engineering, guiding other teams in leveraging the platforms and tools you create.
Collaborate with teams throughout to accelerate AI adoption and productization.

We're hiring a software engineer to work directly with our business teams - finance, sales, legal - building tools and automations that help them do their jobs better. You'll write production code and own what you build, but most of your time will be spent understanding business processes and how to impact them.
Most business teams have more day-to-day operational pain than they realize, and a lot more they could be doing with AI than they know. Your job is to find those gaps and build something that fixes them. Success looks like the team being able to move faster and spend their time on the work that matters, because everything else just runs.
You'll have a lot of autonomy in this role. You'll decide what to work on, build it, ship it, and see whether it actually made a difference. You'll be doing this as part of a small, senior AI team, so while the day-to-day work is independent, you'll have other engineers to collaborate with and a shared bar for how we build things.
What You'll Be Doing:
Build & Engineer:
Take the lead on technical implementation and be the owner of how it all works - picking the right tool for the job (code, no-code, or otherwise) and keeping the knowledge of the system in your handsDesign and deliver end-to-end AI solutions - from first stakeholder conversation through production deployment and iteration
Implement LLM-powered systems: RAG pipelines, AI agents, multi-step automations, and tool-integrated workflows
Integrate solutions with enterprise systems (Salesforce, NetSuite, Slack, Data platforms) and build for production: observable, reliable, and cost-optimized
Embed With the Business:
Work directly with Finance, Sales, HR, Legal, and Customer Success to identify and scope high-leverage AI opportunities
Translate ambiguous business needs into concrete engineering plans; own both the solution definition and the build
Help business stakeholders develop AI fluency and become stronger partners over time

We are looking for a highly skilled AI Engineer to join an advanced R&D environment within the security sector.
Responsibilities:
Develop advanced Python-based systems and integrate a variety of AI models into software solutions.
Implement and deploy AI models in On-Premise environments, including full integration within existing systems.
Work closely with a multidisciplinary team in a dynamic, innovative technological environment.

Join the group that builds the foundation of our companys perception stack. We are looking for a key member to join our Visual GenAI team, dedicated to advancing state-of-the-art research in visual synthesis and Diffusion Models within a high-impact, real-world AV environment.
You will work on cutting-edge AI research in a real-world environment, backed by massive proprietary datasets and large-scale computing infrastructure. Team up with researchers and engineers from various fields to develop GenAI solutions and develop technology with the potential to impact millions of people and save lives
What will your job look like:
Own the full development lifecycle: from training generative models to adapting existing state-of-the-art architecture for concrete, real-world autonomous driving use cases.
Research, evaluate, and improve GenAI and computer vision models with a focus on scalable and clean Python implementation.
Collaborate with cross-functional teams, including AI researchers and perception teams, to integrate synthetic data into real-world AI applications.
Stay up to date with the latest advancements in AI, Generative Models, and Computer Vision.