דרושים » תוכנה » Platform AI Engineer

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 looking for a Senior Software Engineer to own and evolve the runtime platform that powers production AI agents.

This is a hands-on backend and platform engineering role for someone who combines deep TypeScript expertise, strong distributed-systems fundamentals, and exceptional production debugging skills with a practical understanding of LLMs and agentic systems.

You will work closely with engineers building AI agents. Your responsibility will be to provide the reliable runtime, infrastructure, abstractions, and observability they need to deliver new capabilities safely and quickly.

What youll do

Own and evolve the production runtime responsible for executing and orchestrating AI agents.
Design platform capabilities for agent execution, tool calling, streaming, state management, persistence, and long-running workflows.
Build resilient integrations with multiple LLM providers and model-serving platforms.
Design provider-routing and fallback strategies based on availability, latency, quality, and cost.
Implement retries, timeouts, circuit breakers, rate-limit handling, idempotency, and graceful degradation.
Ensure the platform remains available when external dependencies or infrastructure components experience outages.
Build reliable mechanisms for loading, caching, versioning, and recovering agent configurations and artifacts.
Create end-to-end observability for AI requests, including model, provider, agent, latency, token usage, cost, errors, retries, and fallback behavior.
Define dashboards, alerts, SLOs, and runbooks for production AI workloads.
Lead the investigation of complex production issues across application code, infrastructure, external providers, distributed state, and agent behavior.
Improve platform scalability, concurrency, latency, and resource efficiency.
Build reusable APIs and abstractions that allow agent developers to add capabilities without duplicating infrastructure logic.
Strengthen platform quality through integration testing, load testing, failure injection, and dependency-outage simulations.
Turn production incidents into architectural improvements, automated tests, monitoring, and operational safeguards.
Collaborate with product, infrastructure, and engineering teams to translate customer and business requirements into platform capabilities.
Mentor engineers and establish best practices for building and operating reliable production AI systems.

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.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.
This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.
Responsibilities:
AI Agent Design & Integration:
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development:
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure:
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement:
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

We develop the AI infrastructure that powers the AI experience throughout the product. We ensure the production AI platform is stable, reliable and secure.
Our mission is not only to build AI-powered features, but to enable every product team to build reliable, scalable, and high-quality AI experiences.
We work with modern LLM technologies, agentic workflows, MCP, retrieval systems, evaluation pipelines, distributed systems, and production-grade AI infrastructure, deploying to production multiple times a day.
Job responsibilities
What You'll Do
As a Tech Lead, you'll play a key role in shaping the future of AI .
You'll combine deep technical expertise with strategic thinking, helping multiple teams build production-ready AI experiences while driving engineering excellence across the organization.
In this role you will:
Lead the technical direction of one of AI domains.
Design scalable AI architectures and production-ready agentic systems.
Drive technical decisions around LLMs, Retrieval, Tool Calling, MCP, evaluation frameworks, and AI infrastructure.
Own complex cross-team initiatives from design through production.
Collaborate closely with Product, Data, Infrastructure, and Engineering teams to turn AI opportunities into customer value.
Help define engineering standards and best practices for building reliable AI systems.
Drive engineering excellence through architecture reviews, mentoring, and technical leadership.
Balance rapid experimentation with production-grade quality and scalability.
Evaluate emerging AI technologies and identify opportunities to improve our platform and customer experience.

We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.

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.

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.

We Are more than a Professional Services firm, we are a community of people driven by impact. As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies. Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society. About the Role We're looking for a AI backend Engineer with a data science foundation to join our AI team and build production systems that integrate Generative AI capabilities. You'll design and implement end-to-end solutions APIs, databases, orchestration, and cloud infrastructure for clients across a wide range of sectors. This role is ideal for someone who thinks in systems, enjoys working with GenAI technologies, and wants to grow into designing complex architectures. You'll work alongside senior engineers on real delivery projects from day one. Key Responsibilities Design and build backend systems APIs, databases, authentication, and integrations Implement multi-agent architectures and orchestration workflows combining LLMs with backend logic Deploy and maintain systems on GCP, Azure, or AWS Optimize AI system performance, cost, and reliability Collaborate with client teams, DevOps, and stakeholders on project delivery Contribute to technical discussions and solution design