דרושים » AI » Backend Tech Lead - AI Platform

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Key responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

we are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
What you'll be doing:

Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

This is a highly technical, hands-on leadership role for someone who loves solving complex engineering challenges.

You'll lead the architecture and development of our AI initiatives while remaining deeply involved in coding, technical decision-making, and mentoring the engineering team.

If you're passionate about building AI-native products, designing scalable systems, and leveraging the latest AI technologies to accelerate development-you'll fit right in.

What You'll Do:

Design and lead the architecture of complex AI-powered features and services.
Build scalable Full Stack solutions using Node.js and React.
Develop AI-native products using modern LLM technologies.
Drive technical decisions, architecture, and engineering best practices.
Mentor developers through hands-on technical leadership.
Work closely with Product, Design, and Customer Success to deliver impactful solutions.
Explore and adopt the latest AI tools to improve both our product and development workflows.

We are looking for an experienced Backend Team Lead to join our Harmony SaaS Security group and lead the development of our Data Loss Prevention (DLP) platform.
Our team was born from a successful cybersecurity startup acquisition and operates with a startup mindset inside a global cybersecurity leader. We focus on building advanced security solutions that protect organizations from sensitive data exposure across modern SaaS environments.
As a Backend Team Lead, you will own the architecture and evolution of a large scale DLP platform responsible for detecting, analyzing, and protecting sensitive data across thousands of organizations and millions of SaaS events.
You will lead a team of highly skilled backend engineers, working with a modern cloud native stack including Go, GCP, Kubernetes, Kafka, and Postgres, and will design systems that process and analyze massive volumes of security data in real time.
This role combines technical leadership, system architecture, and hands-on development, with opportunities to shape the future of our platform, introduce AI-driven security capabilities, and drive engineering excellence across the team.
If you enjoy building large scale distributed systems, leading strong engineers, and solving complex security problems, we would love to meet you.
Key Responsibilities
Lead and grow a team of backend engineers, fostering a culture of ownership, innovation, and engineering excellence.
Own the technical direction and architecture of the DLP product and its backend services.
Design and build high scale distributed systems that ingest, process, and analyze large volumes of SaaS security events.
Drive architectural decisions around event driven systems, data pipelines, and cloud native infrastructure.
Collaborate closely with product managers, security researchers, and data teams to deliver impactful security capabilities.
Mentor engineers through technical guidance, architecture discussions, and code reviews.
Ensure high standards for performance, reliability, scalability, and observability.
Build and optimize systems leveraging technologies such as Kafka, Kubernetes, and GCP services.
Drive innovation by exploring and integrating AI-based capabilities for advanced data classification and security detection.
Maintain operational ownership of production systems, including monitoring, troubleshooting, and continuous improvements.

We're looking for exceptional backend engineers who understand modern AI systems and enjoy building the infrastructure and products around them.
Our team is creating the foundational technologies that allow AI agents to operate safely, securely, and reliably at scale. This includes building secure agent control planes, embedded controls, developer tooling, observability, and infrastructure that enables production-ready AI systems.
This is a hands-on engineering role for someone who enjoys building products from the ground up. You'll partner closely with AI researchers and backend engineers to rapidly move ideas into production.
What You'll Do:
Design and build secure AI infrastructure for production AI agents.
Develop Agent Control Plane capabilities that manage, monitor, and secure agent execution.
Build embedded controls and security mechanisms directly into AI agents.
Develop reusable services, APIs, and developer tooling that support AI applications.
Build and maintain integrations with modern Agent SDKs and Model Context Protocol (MCP).
Design backend microservices using Python and AWS.
Build observability into AI systems, including telemetry, monitoring, tracing, and operational visibility.
Develop public-facing developer tools and command-line interfaces (CLI).
Partner closely with AI researchers to rapidly transition prototypes into production-ready systems.
Own projects from architecture through deployment.
Help define engineering standards and reusable patterns across the AI platform.
Collaborate with senior engineers while independently leading technical initiatives when appropriate.

Join our AI Platform group as an AI Engineer in the AI Core team and help build the next generation of AI-powered networking and security solutions at our company.
The AI Core team is responsible for developing AI applications, intelligent agents, and backend systems that integrate directly into our company products and workflows. As part of our companys strategic AI direction, the team focuses on turning modern GenAI capabilities into scalable production systems that help customers operate, troubleshoot, investigate, and manage complex networking and cybersecurity environments more effectively.
This role combines strong software engineering, modern GenAI technologies, and deep product impact. Youll work on building production-grade AI systems, integrating LLMs and agentic workflows into large-scale products, and helping shape how AI transforms cybersecurity and networking operations across the company.
We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

Were looking for an experienced Full Stack Team Leader to lead the engineering team behind our Customer Portal-the central platform used by every customer across all of our products. This role reports directly to the VP R&D and combines technical leadership with product ownership, cross-functional collaboration, and execution.

As the engineering leader of the Customer Portal, youll shape one of the companys most strategic products, ensuring customers enjoy a seamless experience throughout their entire journey with us. Youll lead a talented team, drive technical excellence, champion AI adoption, and collaborate closely with stakeholders across Product, Marketing, Customer Success, Support, Sales, and Design to deliver customer-facing capabilities with direct business impact.

Were looking for someone who doesnt wait for direction. You naturally identify opportunities, challenge the status quo, and drive initiatives from idea to execution. You inspire your team through technical leadership, raise the engineering bar, and continuously look for better ways to build products and develop people.

What Youll Do
Lead, mentor, and grow a team of Full Stack Engineers, fostering a culture of ownership, accountability, innovation, and continuous improvement.
Own the technical execution and delivery of the Customer Portal roadmap, serving customers across all our products.
Partner closely with Product Management and business stakeholders to translate strategic objectives into scalable technical solutions.
Collaborate daily with Product, Marketing, Customer Success, Support, Sales, and Design to deliver an outstanding customer experience.
Lead architectural decisions, ensuring the platform remains scalable, secure, maintainable, and ready for future growth.
Drive engineering excellence by establishing high standards for code quality, testing, observability, performance, reliability, and operational excellence.
Champion AI-first engineering practices by driving adoption of AI tools and workflows that improve developer productivity, code quality, and delivery velocity.
Proactively identify opportunities to improve the product, engineering processes, and team effectiveness. Bring ideas, challenge existing approaches, and lead meaningful technical and organizational improvements.
Lead planning, prioritization, estimation, and execution while balancing business priorities with technical investments.
Remove blockers, manage technical risks, and create an environment where the team can consistently deliver high-quality outcomes.
Stay hands-on when needed, contributing to architecture, design, code reviews, and implementation of complex features.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

Were looking for an Engineering Tech Lead to help drive some of the most strategic technical initiatives at our company. This is not a traditional Tech Lead role. Were looking for someone who is deeply technical and highly hands-on, but also knows how to think strategically, lead architecture decisions, and represent the company in front of enterprise customers and senior stakeholders. Youll work across multiple teams and domains, partnering closely with Platform, Product, and Engineering teams to design and deliver AI-powered enterprise solutions at scale. One moment you might be deep in architecture or code, and the next youll be in a room with customer executives helping guide critical technical decisions. We work on site from our offices in Tel Aviv.
What Youll Do
Lead architecture and technical direction for strategic enterprise AI initiatives
Work directly with some of the worlds largest enterprises to design and deliver scalable AI-powered solutions
Partner cross-functionally with Platform, Product, and Engineering teams across the company
Stay deeply hands-on with the code and engineering teams
Drive complex technical decisions across scalability, reliability, performance, and system design
Help customers solve real production challenges and build long-term technical trust
Design versatile enterprise-grade solutions across different customer environments and use cases
Influence engineering standards, architecture practices, and long-term technical direction
Operate in a fast-moving, high-ownership environment where execution speed matters.