לוח משרות דרושים הייטק AI משרה מלאה

We are looking for a senior product manager to join our AI Unit and help shape the AI platform that powers our next generation of products.
This role focuses on the platform and ecosystem layer of AI, building the capabilities, standards, and systems that enable teams across the company to create AI-powered experiences effectively.
You will work closely with engineering, data, and product teams to define how AI capabilities are built, reused, and governed across the platform.
This is a high-impact role with broad scope. It requires strong product fundamentals, technical curiosity, and the ability to operate in an evolving space.
Job responsibilities
Own key parts of the AI platform roadmap, balancing foundational investments with product impact
Help define reusable AI capabilities (e.g., retrieval, embeddings, scoring, agent tooling)
Contribute to shaping how we evaluate, monitor, and improve AI systems in production
Partner closely with engineering on architecture and technical tradeoffs Support the definition of governance and control mechanisms (quality, safety, cost, transparency)
Work with product teams to enable adoption of AI capabilities across the platform
Improve developer and product team experience when building AI features
Contribute to defining standards, best practices, and ways of working for AI across
What makes this role interesting:
You will work on foundational systems that impact multiple product areas
You will help shape how AI is built and used across the entire platform
You will collaborate across teams and influence both product and technical direction
You will operate in a fast-evolving domain with real opportunity to define how things should work.

Required GTM Al Product Manager
About the Role
The GTM AI Product Manager (sitting within RevOps - GTM) translates executive GTM strategy into operational AI solutions, ensuring high-impact initiatives, spanning Marketing, Sales, Partners, and Customer Growth, are successfully defined, scoped, structured, incubated, and brought to life.
Acting as the architect of these initiatives, you translate GTM leadership priorities and target business KPIs into structured execution, connecting business requirements with tech delivery, serving as a strategic bridge and an agile incubator, facilitating rapid prototyping and validation of new workflows.
Job responsibilities:
Responsibilities: Discovery, Architecture & Incubation
Requirement Gathering & Scope Definition: Partner with GTM leadership to gather complex business requirements. Define clear project objectives, use cases, and success metrics (KPIs) while ensuring initiatives stay aligned with top-down priorities.
Functional Architecture: Translate leadership vision into structured operational blueprints and business process flows that define how AI solutions will function within the GTM engine.
Feasibility & Analysis: Lead "buy vs. build" assessments, evaluating market solutions against internal development capabilities to ensure the best path for the business.
V1 Incubation: Build and validate initial prototypes (V1s) using low-code/no-code and agentic platforms to prove value and de-risk the project before scaling.
Scope Integrity: Maintain clarity of scope throughout the execution lifecycle, preventing "project drift" and ensuring technical execution meets the original business intent.
2. Cross-Functional Orchestration
Partnerships: Serve as the primary functional partner for the tech teams to bring AI solutions to production.
Requirement Synthesis: Translate gathered business needs into structured tech requirements, blueprints, and roadmap alignments.
Coordinate implementation: timelines and iteration cycles, ensuring that the final tech delivery matches the functional design and business methodologies.
3. Rollout & Field Excellence
Adoption Planning: Partner with RevOps and GTM leadership to design rollout strategies, communication plans, and enablement materials.

Required Al Infrastructure & Reliability Engineer
What this role is really about
Youll join a 3-person platform team within our Business Technology group -owning the internal infrastructure that our AI platform and its users depend on. This isnt a product engineering role, and it isnt ticket work or babysitting pipelines someone else built. Youre building and operating the internal foundation that the company runs on. The work covers the full stack of platform engineering: core cloud infrastructure (AWS, Kubernetes, IaC), CI/CD pipelines, AI-driven infrastructure components, and the SRE and observability practice that keeps it all honest -metrics, alerting, incident response, and reliability standards. As our AI capabilities grow, so does the complexity underneath them, and staying ahead of that is central to the role. If you treat infrastructure as a product -reusable, automated, observable, and built to last -this is your kind of role.
Job responsibilities
DevOps & AI-Driven Infrastructure - own CI/CD, deployment processes, and release reliability. Build and operate cloud infrastructure that is automated, intelligent, and continuously self-improving - not just managed.
Design and build our Terraform repository and IaC pipeline from scratch -AI-assisted generation, drift detection, and policy enforcement built in.
Build AI-driven GitHub Actions pipelines -automated code review, risk assessment, and intelligent deployment decisions.
Manage Kubernetes workloads across AWS accounts -zero downtime, fully automated, nothing left behind.
Embed AI into the operational layer -proactive drift detection, automated remediation, and intelligent scaling toward a self-healing runtime.
Reliability & SRE -improve uptime, resilience, and incident response.
Define and enforce SLOs/SLIs, error budgets, and on-call practices.
Lead incident response, postmortems, and systemic reliability improvements.
Own AI-specific reliability: model latency SLOs, token quota monitoring, rate limit handling, fallback and retry strategies, and cost-per-request alerting.
Observability & Telemetry - increase visibility, reduce noise, improve troubleshooting.
Establish and continuously evolve the observability stack: metrics, logs, distributed tracing, and alerting tuned for both application and AI workloads.
AI / LLM Operations- bringing AI systems to production and operating them at scale, with a focus on reliability, performance, and trust.
Own the AI infrastructure layer: rate limits, quota management, latency SLOs, and fallback strategies (retries, circuit breakers).
Operate LLM APIs in production with resilience and cost attribution per team/model.

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

we are looking for a AI Backend Engineer.
As the AI Backend engineer , you will join a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll utilize technical skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Design, develop, and maintain backend services for AI agents and tool integrations using latest technologies
Build scalable APIs and microservices that interface with LLMs and AI frameworks
Implement agent orchestration systems, tool calling mechanisms, and workflow engines
Optimize performance and reliability of AI-powered applications at scale
Develop data pipelines for training, evaluation, and monitoring of AI systems
Integrate with various LLM providers (OpenAI, Anthropic, etc.) and manage API interactions

Lead the team building the agentic infrastructure powering Klaudia - our AI SRE. You'll own the architecture, set the technical direction, and push experimental ideas into production.

This isn't a coordination role. You'll be a technical leader who builds alongside your team - setting the bar for architecture quality, driving experimental bets, and turning research into production-grade systems.



What will you do?

Own the agentic infrastructure- You're responsible for the architecture of Klaudia's core - the systems that make autonomous investigation, root cause analysis, and self-healing possible at scale.

Build and grow your team- Hire great engineers, mentor them, run meaningful design reviews, and build a culture of high ownership and engineering excellence.

Drive experimental development- Run structured bets - LLM evaluation frameworks, new agent architectures, novel tool-use patterns - and bring the best ones to production.

Stay hands-on You'll design systems, review PRs critically, and write code where it matters. Your technical credibility is the foundation of your leadership.

Shape our AI strategy- Work closely with product and R&D leadership to define what Klaudia becomes next.



Why this role rocks?

Category-defining work- AI SRE is the hottest space in cloud infra. You'll be leading the team that defines what it means - not catching up to anyone.

Real autonomy- You'll set the technical roadmap for Core. No pre-solved problems handed down to you - you decide what gets built and how.

Build something that lasts- Hire and shape a team from an early stage. Your engineering culture decisions here will compound for years.

Serious engineering culture- High bar for craft, strong team around you, and leadership that respects technical depth over process theater.

Build the future of AI in the world of Cloud Infrastructure. You'll design innovative solutions powered by AI and help shape where we're headed as a company.

Why This Role Rocks:

Develop cutting-edge AI solutions - We're harnessing LLMs to solve real cloud infra problems, not just for buzzword points
We build the future - AI SRE became the hottest market in the cloud infra space - its our job to lead it.
Your ideas become reality - Propose solutions, lead initiatives, and see your impact
Shape our tech direction - You'll have a real voice in our technical strategy.
FULL Ownership: We believe in taking developments end to end. From ideation all the way to production.

We're looking for a technical Product Manager to join AI product team and own the roadmap for Klaudia - our autonomous AI SRE agent. You'll work directly with customers, solution architects and R&D leads to define how Klaudia senses, investigates, decides, acts, and validates across availability issues and reliability risks. It's a role for someone who can translate complex AI/infra tradeoffs into a sharp product strategy.

What you will do

Work on the product roadmap execution, aligned with mission and customer needs
Collaborate with engineering and design teams to drive AI to success
Conduct thorough market research, close work with sales teams and customer calls to identify trends, customer pain points, and opportunities for AI integrations
Effectively communicate product vision, progress, and outcomes to internal stakeholders and customers
Define KPIs around AI capabilities and utilize data-driven insights to make decisions and product iterations

We are looking for a hands-on GTM AI Engineer to design, build, and deploy AI-powered workflows and automations across our go-to-market (GTM) systems.
This role sits at the intersection of business operations and technology, and acts as the engine behind revenue intelligence, process automation, and scalable pipeline generation systems.
You will be a technical force multiplier for our GTM team including creating workflows, agents, and integrations, embedded directly into core business systems (e.g., CRM, marketing automation, support tools).
This is not a traditional software engineering role, but it requires strong technical execution and ownership across the full lifecycle.
What youll do:
Design, build, and maintain production-grade AI workflows and automations to streamline GTM execution (e.g., lead enrichment, routing, research, follow-ups, CRM hygiene, and customer handoffs)
Develop and deploy LLM-based solutions, including prompt-driven workflows, reusable prompt libraries, and AI agents embedded within business systems
Build and maintain integrations and data pipelines across CRM, marketing automation, enrichment tools, and internal systems to ensure reliable, connected data across the funnel
Own workflow performance, review success metrics, iterate and demonstrate business impact.
Build and maintain AI-assisted pipeline inspection tools to give RevOps and Sales Leadership real-time visibility into deal health
Identify opportunities to reduce manual work and improve efficiency across RevOps, Sales, Marketing, and Customer-facing teams
Partner with cross-functional stakeholders to map processes, identify bottlenecks, and prioritize high-impact automation opportunities
Drive adoption through enablement: documentation, training, and ongoing feedback loops
Evaluate and implement new tools and technologies based on ROI, scalability, and maintainability

the role will establish scalable processes, standard pod structures, and PI planning in line with R&D leaderships vision to improve throughput and efficiency. The position will act as a thought leader on agile best practices, supporting R&D leaders through training, documentation, and artefacts, while also ensuring strong visibility into R&D performance through reporting and key metrics such as cycle time, velocity, and throughput. In addition, the role will identify inefficiencies and operational risks, lead mitigation and improvement initiatives, support governance forums, and communicate progress to senior stakeholders, including R&D leadership and senior leadership stakeholders.

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Key Responsibilities:​
Drive the implementation and scaling of SAFe methodologies across R&D, embedding Agile ways of working to improve delivery efficiency and consistency​
Provide thought leadership on Agile best practices, influencing R&D leaders and supporting adoption through training and documentation​
Track and report on key development KPIs (e.g., cycle time, lead time, on-time delivery), identifying inefficiencies and driving continuous improvement​
Design and support governance forums, ensuring clear tracking of actions, progress reporting, and effective communication with senior stakeholders​
Risks and design governance forums, ensuring effective mitigation, progress tracking, and clear communication with senior stakeholders​

We are looking for a technically-grounded, visionary Product Owner to lead GenAI-powered initiatives within our B2B platform. You will stand at the intersection of cutting-edge LLM technology and enterprise-scale business impact, transforming how global financial institutions handle everything from underwriting automation to complex claims intelligence.

Key Responsibilities:
AI Roadmap & Strategy: Define and own the GenAI roadmap, identifying high-value use cases like fraud detection copilots, document intelligence, and agentic underwriting.
Backlog Excellence: Own and optimize the product backlog, translating complex AI concepts into clear user stories and acceptance criteria for engineering and data science teams.
Technical Specs & Orchestration: Read and write technical specs, API contracts, and data models. Youll work closely with Development & architecture teams
Experimental Mindset: Lead lean experiments and A/B tests to validate LLM performance, managing the balance between probabilistic AI outputs and deterministic business rules.
Stakeholder Leadership: Communicate the vision and progress transparently to global stakeholders and enterprise clients, acting as the bridge between "the possible" and "the practical".

Support the implementation of the AI strategy across R&D by identifying, selecting, and institutionalizing AI tools to drive efficiency across the SDLC​
Partner with R&D and Product leadership to drive adoption of AI tooling, developing training materials, use cases, and leading enablement sessions across divisions/product teams​
Define and track KPIs to measure AI impact (e.g., financial benefits, development efficiency, quality improvements), providing visibility on realized value​
Establish and maintain governance frameworks, artefacts, and AI usage policies in collaboration with R&D Ops and SecOps to ensure structured and compliant adoption​
Identify operational risks related to AI adoption, driving mitigation plans and supporting governance forums to track progress and communicate with senior stakeholders​

Were looking for a seasoned R&D Team Leader to join our top-notch technology R&D team, reporting directly to the VP R&D. In this role, you will drive technological innovation, oversee the development of cutting-edge features, and guide the team in delivering scalable, high-quality products. You will combine hands-on technical leadership with strategic oversight, ensuring that our platform continues to evolve and deliver impactful solutions for our clients. As part of an AI-first company, our web team is deeply involved in creating and integrating AI-driven features to enhance our digital offerings.



Key Responsibilities:

Lead the R&D team in developing new features and enhancing our platform.
Oversee the end-to-end development lifecycle, from ideation to deployment.
Ensure high-quality code, scalable architecture, and smooth product delivery by implementing best practices in software development.
Mentor and support team members in their professional growth.
Troubleshoot and resolve complex technical challenges in collaboration with the team.
Collaborate with cross-functional teams including Product, Data, and AI to align development efforts with company goals.
Drive innovation and stay updated on new technologies to keep us at the forefront of the industry.

Were looking for a Software Engineer - Data Operations Platform to join our Data Operations team and help build the internal systems and platforms that power our data workflows at scale.

This is a unique opportunity for an early-career engineer who enjoys solving practical problems, building impactful tools, and working closely with data, AI, and operations teams. In this role, youll design and develop scalable internal platforms, automation systems, and AI-driven workflows that support large-scale data operations, including tooling for computer vision workflows, automated QA systems, taxonomy management, and database navigation tools used daily across the company.

As part of a fast-moving startup and an industry leader in AI-driven creative analytics, your work will have a direct impact on engineering efficiency, workflow automation, system scalability, and data quality.



Key Responsibilities

Design, develop, and maintain internal tools and systems that support Data Operations workflows.
Build scalable automation systems for QA processes, taxonomy applications, and large-scale data handling.
Collaborate closely with Data, AI, Product, and Operations teams to solve practical business and operational challenges.
Write clean, maintainable, and reliable code with a strong focus on usability, scalability, and efficiency.
Improve internal workflows by identifying bottlenecks and building scalable solutions.
Work with databases and data pipelines to support operational and analytical needs.
Troubleshoot issues, optimize existing tools, and continuously improve system reliability and performance.
Contribute ideas, experiment with new technologies, and help improve developer workflows and internal processes.