לוח משרות דרושים הייטק AI  בתל אביב יפו, לחיפוש זה נמצאו 128 משרות

We are a fast growing tech company in the automotive space with hubs across the US and Israel. We are disrupting the multi-trillion dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal driven, and, at our core, we believe every voice has value and can impact our bottom line. If you are a creative, solutions oriented individual who is ready to put your career in drive, we are the place for you! We are seeking a Prompt Engineer to join our product team and help take our AI-powered products to the next level. In this position you will be responsible for ensuring that our LLM workflows not only meet the highest standards of quality and reliability, but actively drive conversion and adoption across our products. You will design, validate, monitor, and optimize prompts, LLM workflows, and AI agents, with a sharp eye on business outcomes and conversion rates. The ideal candidate will possess excellent organizational and communication skills, a strong product and growth mindset, and the ability to collaborate effectively across many departments and teams. Most importantly, you will be genuinely passionate about modern AI tools and the practical adoption of LLMs in product development: you stay on top of what's new, experiment constantly, and bring fresh ideas to the team. This is a position based out of our Tel Aviv office or Jerusalem office, and will report to the LLM team lead.

What you will be responsible for:

* Design, prototype and iterate AI agents and LLM workflows from ideation to execution
* Drive conversion rate optimization (CRO) and product adoption for AI agents
* Monitor live systems (dashboards, A/B tests, validation pipelines), triage issues, and implement fixes for hallucinations and regressions
* Build and maintain LLM-as-judge frameworks to continuously evaluate quality at scale
*  QA and evaluate end user-facing AI output with a sharp eye on tone, messaging, and conversion effectiveness
* Collaborate with stakeholders across product, marketing, CX, and R&D teams

The top candidate will also have:

* Hands-on experience with using LLM pipelines in a product context
* Experience working with chatbots or conversational AI products
* Writing experience, such as copywriting, personal writing, UX writing background
*  JavaScript or basic scripting knowledge


Why you should join us:

* An awesome global team of forward-thinking, innovative go-getters
* Integrate with tech titans: work directly with APIs from Google, facebook, Microsoft, and more
* Be part of a rapidly scaling company poised for the future
* Learning and growth opportunities within a fast-paced tech startup environment
* Clear career advancement path for strong performers
* We are committed to setting each other up for success. As a member of our team, you will work in an environment that encourages growth, initiative taking, and continuous mutual feedback in order to reach your full potential.
* Cibus and lots of yummy treats:-)
Are you the one? apply here!

As an AI Productivity & Implementation Specialist, you will partner with business units across our company to identify where AI can eliminate friction, accelerate processes, and create measurable efficiency gains. You will not just recommend. You will build, deploy, and own the solutions end to end.
This is a high-visibility role in a team that reports to the COO. Your work will be measured in business outcomes, not activity.
What You Will Do
Partner with business unit leads and department heads to map their end-to-end processes, identify inefficiencies, and assess whether a process should be eliminated, redesigned, or enhanced with AI.
Design and deploy AI-powered automations and workflows using no-code and low-code tools (e.g. BlinkOps, n8n, Claude Cowork, GPT integrations, or similar).
Run AI productivity projects from discovery through deployment and adoption, owning the full lifecycle.
Inspect end-to-end organizational processes and evaluate whether they are needed, broken, or candidates for AI enhancement.
Translate business problems into clear AI solution briefs and present recommendations to non-technical stakeholders.
Develop organizational learning tools and lead training sessions to ensure employees actually use the AI solutions you deploy.
Track and report measurable outcomes: time saved, cost reduced, error rates reduced, cycle times improved.

Were on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building the AI application foundation behind our next-generation cyber-AI product.
This team owns the core backend and frontend infrastructure that powers all user-facing applications - as well as the agentic and conversational frameworks that bring intelligence and automation into the experience.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the systems that enable every other Engineering group to create fast, scalable, and intelligent apps on top of our platform.
Responsibilities
Lead a multidisciplinary team responsible for backend services, frontend frameworks, and AI agent infrastructure - the technical bedrock of our product experience.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and build robust frameworks and systems that power all customer-facing applications.
Develop the agentic and conversational architecture enabling LLM-powered user interactions and intelligent workflows.
Collaborate with AI research, data, and product teams to seamlessly integrate AI-driven capabilities into production systems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.

We are seeking a Senior AI Engineer to join our companys core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within our companys Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
Responsibilities
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Design and build complex, interactive UIs with React, TypeScript, and Next.js.
Apply design engineering principles to translate Figma designs into highly polished, responsive implementations.
Own component architecture: build reusable, composable, and well-documented components.
Own production health and observability to ensure system reliability at scale.
Ensure accessibility and cross-browser compatibility.
Write tests and maintain code quality across the frontend codebase.
Collaborate with design, backend, and product teams to ship features end-to-end.
Mentor engineers and promote frontend engineering best practices.
Leverage Al-assisted development tools to accelerate workflows and improve code quality.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team at our company the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Open Research Tracks
We are hiring across the following specializations. We expect depth in at least one area and the intellectual range to collaborate across them.
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Define and execute a research within your track, experiments, quality gates, and upper bounds in rigorous manner.
Collaborate across tracks on system integration and cross-disciplinary research.
Collaborate work with engineering teams until production.
Mentor junior researchers and contribute to a culture of technical excellence.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

We are looking for an AI-first Software Engineer who is highly product-oriented and excited about building customer-facing systems using modern AI tooling to dramatically increase development speed and operational automation.
What youll do?
Build and ship end-to-end product features (backend, frontend, integrations, automation).
Use AI tools and build the AI infrastructure to accelerate development through scalable workflows, including multi-agent approaches.
Build AI agents that fully automate customer-facing sales and service flows, in a business with a massive volume of textual interactions.

we are looking for a AI/ML Applied Researcher.
As AI Applied Scientist, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore, research, and develop cutting-edge solutions that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team, you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the technologies in the world, witnessing firsthand their impact on our customers.
A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Research, design, and build anomaly classification, predictive, insights, recommendations, and other types of models from various data sources, including sensor time-series data, textual data, images, and more.
You will Ensemble multi-modalities by exploiting and enriching the most from our data collections platform and feature extraction and store phases, using classic statistical methods, deep learning, Transformers, Graphs, Foundations Modules (as TSFM, Graph Transformer, TGNN), and any available technology to extract recommendations for taking real-world, life-changing actions.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Work with cloud-based big data platforms for training, distributed processing & experiments tracking (e.g., Metaflow, Grafana, Outerbounds, Databricks).
Partnering and contributing to modern technologies: LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.
As part of our hybrid working policy, you will be expected to work from the office at least twice weekly, which includes at least one day in Haifa.

We are looking for a visionary and execution-oriented AI Product Manager to shape the unified agentic experience across the Bob platform, redefining how users interact with software, complete work, and discover value through AI.
This role owns the AI product experience and agentic behavior layer of the platform, ensuring AI capabilities translate into intuitive, trusted, and high-impact workflows for customers.
Rather than simply adding AI features into existing workflows, your mission is to help define an AI-first product experience where agents, automation, orchestration, and conversational interactions become a natural part of how work gets done across HR, Finance, Payroll, and beyond.
Youll work across product, engineering, design, data, and domain teams to invent new interaction patterns, drive adoption of AI-powered workflows, and help shape the future operating model of the Bob platform.
This role is ideal for a product leader who is deeply curious about AI, actively uses AI tools in their daily work, and is excited about rethinking product experiences from first principles.
Job responsibilities
Lead the evolution and adoption of the unified agentic experience across Bob
Define AI-first interaction models, workflows, and user journeys across the platform
Shape how users discover, trust, adopt, and repeatedly engage with AI-powered workflows and agents
Drive behavioral change toward AI-first ways of working across the platform
Identify high-value cross-domain workflows and opportunities for automation
Lead discovery and experimentation around emerging AI capabilities, workflows, and interaction paradigms
Partner closely with design and engineering to invent intuitive and high-utility AI experiences
Define how agents reason, orchestrate capabilities, and execute meaningful workflows across domains
Translate advanced AI capabilities into practical and valuable customer outcomes
Use product analytics, behavioral insights, and customer feedback to continuously improve the experience
Collaborate closely with platform teams to ensure AI capabilities can effectively power customer-facing value
Help shape the long-term vision of AI across the Bob platform.

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.