דרושים » AI » Senior AI Engineer

We're building AI to tackle one of the hardest operational challenges in business: getting workforce management right across many markets, each with its own tax rules, labor laws, payment rails, and constantly shifting policies.
In this role on our AI team, you'll focus on agentic workflow automation. You'll design, build, and deploy reliable AI agents that automate complex HR, payroll, and payment workflows, handling decision-making, document intelligence, and complex tasks that typically require human judgment.
What You'll Do:
Design and build agent-based systems that automate document processing, business insights, and complex enterprise workflows
Build observability, evaluation, and feedback loops for agent behavior to improve reliability, accuracy, and trust in production
Own the technical architecture and engineering standards for agentic systems
Build or manage data pipelines to process large volumes of documents and unstructured data
Collaborate with domain experts to identify high-value automation targets and deliver end-to-end solutions
Stay current on agent frameworks, LLM capabilities and limitations, and apply emerging patterns pragmatically in production

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.

Join our Analytics Research team and help shape next-generation Customer Engagement and Interaction Analytics solutions. You will design, research, and productionize advanced NLP and agent-based AI capabilities that autonomously reason, plan, and act across complex customer interaction workflows.
Youll work end-to-end-from foundational research and rapid experimentation to scalable deployment-building systems that combine LLMs, tools, memory, and orchestration to deliver trusted, enterprise-grade AI used by customers worldwide.
What Youll Do:
Research, design, and develop state-of-the-art NLP, LLM, and Agentic AI systems
Build and evolve autonomous and semi-autonomous agents for interaction analysis and customer engagement use cases
Advance analytics capabilities using reasoning, planning, tool use, and multi-agent collaboration
Tackle complex research problems over large-scale conversational and multimodal data
Collaborate on broader analytics initiatives, including scalable ML systems and data-intensive pipelines
Design and run experiments, evaluate agent behavior and model quality, and communicate results clearly
Take solutions from prototype to production, balancing research innovation with robustness and performance

Required Senior AI-Native Software Engineer
Role summary:
You will join a high-impact AI engineering team within R&D, owning problems end-to-end from understanding the business need, through architecture and implementation, to production monitoring. This is a new way of working: you'll work directly with business stakeholders, ship AI-driven capabilities at speed, and help define the methodology as we build it.
As a member of the AI Foundations organization, you will lead best practices, champion early adoption of new technologies, and influence the direction of our R&D guild - building and shipping cutting-edge agentic applications that deliver seamless experiences to our users.
Location:
Hybrid - Herzliya, Israel
Full-time
What you'll do:
Own the full development loop understand the business problem, define the solution, architect it, build it, ship it, and monitor it in production
Use AI as your primary development tool, achieving in a day what used to take a team a week
Collaborate with your team and business stakeholders to define decision logic, risk thresholds, and success metrics
Design and build evaluation frameworks as part of every solution you don't ship what you can't measure
Own production readiness monitoring, alerting, and observability go in on day one
Contribute to shaping team practices, tooling, and engineering standards across the pod
Decompose business problems into agentic workflows, orchestrated flows, and reusable capabilities.

Were expanding our Data & AI group and looking for a passionate, experienced Senior Data & AI Engineerto join our mission. This is a unique opportunity to work at the intersection of data engineering, LLMpowered systems, agentic workflows, and cybersecurity innovation

What youll work on
Data Infrastructure & EngineeringDesign, build, and scale production-grade data pipelines using Databricks, Spark, and modern cloud-nativetechnologies. Ensure high standards of data integrity, system performance, reliability, and scalability.
Core Backend & PlatformDesign and contribute to scalable backend services and platform capabilities using microservices andevent-driven architectures. Build reliable APIs, integrations, and asynchronous data flows that support highscale AI, data, and cybersecurity use cases.
LLM & Agentic SystemsDesign, prototype, and integrate LLM-powered systems, including Retrieval-Augmented Generationpipelines, agentic workflows, tool-using agents, multi-step reasoning flows, and AI-driven automation. Workwith technologies such as AWS Bedrock, OpenAI, Anthropic, LangGraph, vector databases, and modernorchestration frameworks.
AI-Assisted Engineering & Developer ProductivityExplore and apply advanced AI coding assistants and software-engineering agents, such as Codex andClaude Code, to improve development velocity, code quality, debugging, testing, and experimentation.Build proof-of-concepts and internal tools that help engineering and research teams work more effectivelywith AI-powered development workflows.
Intelligent Cybersecurity FeaturesCollaborate with Security Researchers, Engineers, and Product teams to identify opportunities forintelligent, data-driven features that deliver actionable cybersecurity insights to customers. Transformcomplex cybersecurity and platform data into reliable, explainable, and useful AI-powered capabilities.

As a member of our fast-paced group, youll have the unique and rewarding opportunity to shape the future. We are looking for people with excellent applied machine learning, NLP experience and solid engineering skills.

This role will have the following responsibilities:
Developing and integrating AI systems (e.g RAG, agents) into deliverable products.
Developing and evaluating domain specific Large Language Models for various tasks and applications.
Understanding product requirements, translating them into modeling tasks and engineering tasks.
Collaborating with Hardware and Software teams across us.
Translating theoretical ideas into tangible innovations.

Build Modular AI Capabilities: Design and implement self-contained "AI Skills" that connect to the Platforms core data layers.
Ship End-to-End Autonomous Agents: Build agents that don't just "think," but act. You will deploy agents that handle the heavy lifting of the security lifecycle.

Bridge the Gap to Non-Technical Users: Create the abstractions that allow our customer success teams and client stakeholders to trigger or chain these AI workflows.

Own the AI Infrastructure & Evaluation: Maintain and contribute to the environment where these agents are born, ensuring they are grounded in truth.

We are seeking a highly motivated AI Solutions Engineer to join a team leading the evaluation, adoption, and integration of AI-based tools into our development processes.
This role involves identifying opportunities to enhance workflows through AI, implementing internal tools that leverage AI capabilities, and collaborating with cross-functional teams to ensure seamless integration and usability.
Responsibilities:
Lead end-to-end AI initiatives from ideation to production
Design and deploy AI agents, automations, and data-driven solutions
Partner with business and engineering teams to deliver impactful use casesDrive prioritization based on business value and strategic impact
Define KPIs and monitoring to track performance, adoption, and ROI
Provide insights to leadership and lead cross-functional efforts in a matrix environment
Lead technical AI sessions, workshops, and internal enablement programs to drive adoption and upskill teams.

We are looking for a talented and curious ML Data Scientist to join our growing Machine Learning team in Herzliya.

In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected.
Responsibilities
As an ML Data Scientist on this team, you will play a central role in shaping the data that powers our ML models. You will:
Investigate model failures - identify patterns, hypothesize root causes, and work with the team to implement fixes
Own data curation: evaluate, clean, and curate datasets to maximize model training quality
Design and execute experiments end-to-end: from defining the question and data collection escort, through analysis and statistical validation, to presenting clear conclusions and driving implementation
Define data collection strategies - collaborate with others to decide what data we should be collecting and why
Design and maintain monitoring solutions with others to ensure ongoing data quality and integrity at scale