דרושים » AI » Head of AI

We are looking for a mission-driven BizOps Engineer to join our R&D team!
We specialize in advanced AI predictive models, focusing on LTV, churn, and intent to drive business growth.
As the BizOps Engineer, you will serve as both a platform architect and a hands-on builder. You will own the AI-native platform architecture and governance for all non-core product functions, including Sales, Operations, HR, Legal, and Finance, while also building, maintaining, and scaling custom AI solutions yourself to address specific departmental needs.
Reporting directly to the VP of R&D, this role begins as a high-impact Individual Contributor (IC) with a clear mandate to build and lead a dedicated engineering team as the function scales. Your primary focus will be designing and deploying infrastructure and security protocols while simultaneously delivering the bespoke AI tools that empower teams and drive operational efficiency.
You will have the autonomy to choose the most effective path forward for any given challenge, whether that means leveraging existing SaaS platforms, integrating open-source projects, or building custom solutions from scratch, always guided by the specific needs and projected ROI of the departments you support.
Responsibilities:
Architect and maintain the internal AI-native platform, while personally building and scaling custom AI solutions and automated workflows for cross-functional teams.
Establish and enforce security protocols, governance frameworks, and best practices to enable safe and compliant AI solution development across the organization.
Identify and scale platform enablement opportunities that allow departments to automate their own workflows using approved AI capabilities.
Monitor and manage organizational compliance for internal AI applications, ensuring data privacy and ethical standards are met at scale.

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.

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 looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

We are seeking a strategic technical leader to drive the next phase of our engineering evolution. Reporting directly to the VP of R&D, you will carry two core mandates:
Manage one or more engineering teams with a focus on AI development.
Lead AI SDLC transformation efforts across the entire R&D organization.
This is a rare, high-leverage role at the intersection of people leadership, technical craft, and organizational transformation. If you want to define how an entire engineering organization works in the age of AI - and leave a lasting fingerprint on a fast-scaling SaaS platform - this role is for you.
What You'll Do:
Domain Ownership & People Management:
Assume operational leadership for critical R&D domains, including management of engineering teams focusing on AI.
Manage, coach, and grow Team Leads and senior engineers, building leadership depth across your domains.
Own team health, delivery velocity, and engineering quality for every team under your purview.
AI Developer Experience (AI DX):
Lead the transformation of our engineering processes by implementing AI-driven tools, frameworks, and workflows.
Significantly accelerate R&D throughput, optimize developer workflows, and foster an AI-first engineering culture - leading by example.
Drive adoption of agentic coding tools (e.g., Cursor, AI agents) across teams and measure their impact on productivity.
Technical Authority & Governance:
Challenge existing architectural paradigms and introduce innovative, out-of-the-box solutions to complex technical problems.
Mentor engineering teams and raise the bar for AI engineering quality and best practices across R&D.
Strategic Cross-Team Leadership:
Orchestrate complex, cross-functional initiatives that require deep technical alignment across disparate teams.
Manage project delivery, timelines, and execution to ensure seamless cross-functional results.
Architectural Vision:
Define and execute the long-term technical AI roadmap, ensuring high standards of scalability, reliability, observability and engineering excellence across the platform.

Were growing and looking to hire a Director of Data & AI who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.
About the Company:
A global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. Were a fast-growing, award-winning team where innovation meets purpose-and we want you to help us define the future of cybersecurity.
Our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all our products, delivering deep visibility across CPS environments-without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments.
About the Role:
We are seeking a visionary Director of Visibility to lead our core technology engine. This is a highly unique role that demands both top-tier professional expertise in cybersecurity research and the ability to seamlessly integrate Data Science and AI in a precise, highly productive manner. We have ambitious visibility goals that require uncompromising accuracy. Your mission is to combine precise, in-depth professional understanding of Cyber-Physical Systems (CPS/XIoT) with the immense scale and capabilities of AI. You will lead a multidisciplinary group comprising Data Science, Network/Protocol Research, and Asset Classification teams to revolutionize how we discover, classify, and secure critical assets across industrial (OT) and healthcare (IoMT) environments.
Responsibilities
As a Director of Data & AI your impact will be:
Multidisciplinary Leadership: Manage, mentor, and synchronize three distinct teams (Data Science, Network Research, and Asset Classification), ensuring cross-functional synergy and unified product delivery.
Scaling Accuracy with AI: Architect our visibility solutions to achieve unparalleled precision. Blend deep professional domain knowledge with advanced ML to scale asset discovery without sacrificing the exactness required in critical infrastructure.
Feature Engineering & Parsing: Oversee the translation of obscure, undocumented industrial and medical protocols into actionable features for our AI models.
Cross-Department Collaboration: Work closely with various data groups, product management, and R&D teams to translate network visibility into actionable risk management, segmentation, and threat detection policies.
Advanced Data Fusion & Collection Strategy: Manage diverse collection techniques (passive, active, and integrations), and architect how to fuse information for every single device at the scale of AI-bridging applications, algorithms, LLMs, and beyond.

We are looking for a Hands-On Agentic AI Engineer (Information Systems Team) to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.

The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.



Responsibilities:

Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations