דרושים » AI » Director - Agentic Search & Data Infrastructure

We're looking for a Senior Team Lead to own two things at the core of our product: the data-pipeline infrastructure that ingests and processes web data at scale, and the agentic AI system that generates Extraction Templates - the mappings that turn any webpage into structured data.

You'll lead a team of 6 engineers spanning Backend, Full-Stack, and AI - coaching, managing, and hiring across both disciplines while staying hands-on, not just directing from a distance. Exceptional internal leadership and people skills are a must: clear communication and real ownership of team health, not just delivery.

What Youll be Doing:

Data Pipelines at Scale
Own end-to-end architecture and delivery of our data-pipeline infrastructure - from system design to large-scale data flow, storage, and operations - already running in production for Fortune 500 customers.
Continuously analyze and improve the efficiency, scalability, cost, and stability of pipeline components as volume grows by an order of magnitude or more.
Design and implement supporting interfaces (Skills, Plugins, MCP, UI, API) and platform engineering where needed to deliver pipeline capabilities end-to-end.
Partner closely with the Product and Delivery team to define and prioritize the right pipeline solutions.

Agentic Generation of Extraction Templates
Bring deep, hands-on expertise in LLMs, agentic architectures, evaluation/benchmarking, and modern AI/LLMOps practices; make build-vs-buy and architecture calls with authority.
Grow the team's AI capability day to day: actively promote and mentor AI-native development practices.
Continuously improve the Extraction Template generation capability's coverage, accuracy, and scale.

We need a Director to set the strategy for everything underneath it - cloud, security, and the delivery lifecycle - and to bring AI into how that infrastructure is run.

This is a director-level leadership role, not an IC stretch assignment. You will lead our DevOps organization - which already has a team leader running day-to-day delivery - and operate one level up: setting direction, owning the roadmap, making architecture and build-vs-buy calls with authority, and representing infrastructure at the leadership table. Close enough to the work to guide it in depth, senior enough to own it end to end.

What Youll be Doing:
Own cloud infrastructure and security as one strategy: architecture, scale, and the path to our next order of magnitude of growth, with our security and compliance posture (IAM, secrets, hardened baselines, SOC 2 / ISO 27001 audit readiness) built in from the start, not bolted on.
Own the SDLC end to end, and drive AI into every stage of it: measure delivery performance (lead time, deployment frequency, change failure rate) and use AI to improve each stage of the lifecycle - planning, code review, testing, release, and operations - alongside AIOps practices like automated/self-healing recovery and intelligent alerting.
Own FinOps as a strategic discipline: the cloud bill is a P&L line you're accountable for, with unit economics driven down every quarter.
Own vendor and contractual relationships across cloud, tooling, and infrastructure services - negotiating leverage, not just approving invoices.
Lead the DevOps organization through its team leader: set technical direction and standards, develop the team leader into a stronger manager, and grow the bench beneath them.
Partner as a peer with Backend, Infra, AI, Data, Product, Security and Finance leadership - infrastructure decisions get made with you in the room, not after.

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

We're looking for a Head of Research to establish and lead our research group - a strategic and hands-on leadership role for someone who thrives at the intersection of AI, infrastructure, and systems innovation. You'll identify high-impact research directions, validate cutting-edge technologies, and drive new approaches that translate into long-term competitive advantage for us. This is not an academic position, but an opportunity to build a research function that directly shapes product and technology.

Define and lead the company's research agenda in AI, infrastructure, and distributed systems.
Explore and evaluate new algorithms, architectures, and approaches relevant to large-scale AI workloads and cloud cost efficiency.
Collaborate with product and engineering to translate research into real-world impact.
Build and manage a small, high-caliber research team.
Publish findings, represent us in the AI/infrastructure research community, and establish partnerships with academia and industry.
Act as a thought leader driving innovation across the company.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power our companys conversational products.
Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.
In this role, you will:
Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

As an Engineering Manager at Cortex Cloud, you will lead a team of ~6 engineers operating in one of our most complex and cross-functional domains. This role requires a strong blend of people leadership and deep technical expertise, including systems design and large-scale distributed cloud architectures. You will be responsible for driving the design and delivery of complex, high-impact systems, while ensuring the team executes against the roadmap with both speed and engineering rigor.
Key Responsibilities
Build, mentor, and lead a high-performing software engineering team, fostering a culture of empowerment and driving both individual growth and collective impact.
Partner closely with Product Management and cross-functional teams (Infrastructure, Research, UX) to define priorities and shape multi-quarter product roadmaps, ensuring alignment across all stakeholders.
Own the end-to-end software development lifecycle, translating product strategy into executable plans and ensuring consistent, high-quality, on-time delivery.
Provide architectural leadership for scalable, distributed systems operating at petabyte scale, guiding the design and implementation of high-throughput, cloud-native backend microservices.
Drive production readiness by enforcing best practices around deployment, observability, reliability, and runtime stability, focusing on the details to ensure operational excellence.
Align stakeholders across business units through clear communication of technical strategy, trade-offs, priorities, risks, and execution plans.
Engage directly with strategic customers to lead technical deep dives and architecture reviews, and to influence future product direction.
Foster a culture of high engineering standards, accountability, and continuous improvement, with a strong emphasis on quality and security.

We are seeking a Head of Research to build and lead our research group reporting to the Co-founder and CTO. You'll set the research agenda for how AI agents, spanning coding agents, SaaS AI platforms, cloud, and endpoints, can be abused, and you'll turn that research into the detections and runtime protections that define our product. You'll build the team, the threat intelligence function, and the processes that keep us ahead of a threat landscape that changes weekly. This is a hands-on leadership role. You'll still go deep on platforms and attack paths while scaling research into a core differentiator of the company. You will help define the field of Agentic Security and be one of its leading voices.

Responsibilities

Lead and grow the research team: Hire, mentor, and manage AI security researchers. Build a culture of rigor, speed, and ownership.

Own the research direction: Proactively identify emerging agentic threats and platforms, prioritize research projects, and set a roadmap aligned with product and customer needs.

Build threat intelligence processes: Establish how we collects, triages, and operationalizes threat intelligence on agentic attacks. This includes in-the-wild abuse, malicious MCP servers, skills and extensions, and new techniques from the research community.

Drive research into product: Partner closely with engineering and product so findings become production detections, runtime policies, and governance capabilities. Own the coverage and quality of our detection logic.

Define detection strategy: Set standards for detection logic across environments, including coverage models, efficacy measurement, and false positive and false negative management at enterprise scale.

Stay hands-on: Lead deep dives into platform architectures, monitoring and enforcement boundaries, and end-to-end PoCs for the most critical attack paths.

Represent us externally: Publish research, advisories, and vulnerability disclosures. Speak at leading security conferences and build our reputation as the authority on agentic security.

Support customers and the field: Provide research expertise for customer engagements, incident investigations, and strategic accounts.

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.

You will be part of the Platform team, reporting to the VP of R&D. This is a hands-on IC role at the crossroads of data science, software engineering and cloud infrastructure: you design the service, you build every layer of it, you ship it, you measure what it does for the products that use it, and you maintain and extend it with the features its users need.
Responsibilities
Own services end to end: From a one-page design through API, SDK, UI and infrastructure to production, built to the platforms service standards: tested at every level, auto-deployed on merge, with live status and cost per job.
Build data services at scale: Spark and EMR jobs over the lakehouse, orchestrated in Airflow, that resolve identities, join vendor feeds and score millions of records per run, and that get faster and cheaper with every release.
Put models and LLMs into production: Foundation model, embedding, classification and agent services, each with an evaluation harness behind it, so a model change is measured before a product feels it.
Build the full stack: Backend services, web consoles and SDKs that an engineer, a product team or an agent can use self-serve, with a user guide for people and a playbook for agents.
Run what you ship: Monitoring, alerting, retries and cost per job. You are the first responder when your service is red, and you announce every release to its users with measured numbers.
Work AI-native: AI coding agents are part of how we build every day. You drive them, review their output critically, and build services that agents consume as easily as people do.

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.