דרושים » תוכנה » AI System Architect

The Architect leads the design and implementation of scalable AI platforms and central services for AI, creating shared capabilities, tools, and frameworks that transform how our company builds, delivers, and operates products.
Beyond architecture, this role drives strategic, high-impact projects with powerful ROI that positively disrupt operations and elevate customer outcomes, improving efficiency, innovation, and product value across the company.
Strategic Objectives:
Accelerate AI Transformation across the organization by designing and operationalizing central AI services and a unified platform framework that powers key transformation initiatives, including Agentic Workflows.
Institutionalize AI Engineering and Governance Standards through common architecture, services, and enablement frameworks ensuring scalability, security, quality, and compliance.
Deliver measurable transformation outcomes through strategic, ROI-driven projects that reshape how our company's products are built and operated, directly benefiting customers and business performance.
Drive sustainable transformation at scale, balancing rapid innovation with operational excellence and long-term maintainability.
Key Responsibilities
Architect the AI Transformation Framework
Design and own the end-to-end architecture that enables the companys AI Transformation vision - spanning data, models, pipelines, APIs, and governance layers.
Define blueprints and integration standards to embed AI and automation throughout the SDLC, from ideation to delivery.
Build Generative AI Platforms and Central Services
Lead the design and implementation of the AI Enablement Platform and central AI services powering transformation initiatives such as Agentic Workflows and the Knowledge Hub.
Create scalable, secure, and modular AI components that can be leveraged across product lines and engineering domains.
Partner with infrastructure, platform, and security teams to operationalize LLM-based services, retrieval systems, and agentic automation flows.
Drive Strategic Transformation Projects
Lead cross-functional initiatives that deliver tangible operational and business impact - improving speed, quality, and cost-efficiency across the product organization.
Develop strong business cases and ROI frameworks to prioritize and communicate transformation value at the executive level.
Translate successful outcomes into reusable playbooks and AI cookbooks that scale across teams, roles, and product domains.
Technical Leadership and Enablement
Act as the senior technical authority and coach for AI transformation initiatives, guiding teams through architecture reviews, proofs of concept, and scale-up phases.
Mentor internal architects and tech leads to develop AI-native architectural competencies.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.

Your Impact
AI Agent Development

Design and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management.

Implement reinforcement learning techniques to enhance decision-making capabilities of AI agents.

AI Integration

Build and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM).

Use frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing.

Data Processing and Pipelines

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently.

Optimize data handling to improve speed and accuracy of AI agents.

Security and Compliance

Implement authentication and authorization mechanisms to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling.

Cloud Infrastructure and Scalability

Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.

Leverage containerization (Docker, Kubernetes) for efficient deployment and management.

Testing and Optimization

Develop and execute unit, integration, and performance tests for AI-driven systems.

Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.

Collaboration

Work closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements.

Participate in code reviews, design discussions, and architecture planning to drive innovation.

We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv.
This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company.
What Youll Do:
Design and build reusable AI platform capabilities used across multiple products.
Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities.
Design and build internal AI platforms such as organizational knowledge (Brain), AI developer tools, autonomous engineering workflows, and shared AI services.
Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform.
Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities.
Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment.
Build and operate production AI services using modern cloud-native technologies.
Improve the reliability, scalability and observability of AI systems.
Define engineering standards, reusable patterns and best practices for AI development across engineering teams.
Lead technical proof-of-concepts and drive adoption of innovative AI technologies.
Mentor engineers and provide technical leadership on complex AI initiatives.

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 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.

We are looking for a Senior Data Architect to help define and evolve the data architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable data systems, set technical direction for how data is ingested, modeled, stored, and served, and guide teams in making high-quality architectural decisions that balance delivery speed with long-term sustainability.
This is a hands-on, senior technical leadership role: you will spend most of your time shaping data architectures with teams, reviewing data models, pipelines and critical code, and driving shared standards and patterns across the organization, all in an advanced agentic environment.
Responsibilities:
Define and evolve the data architecture for key domains (ingestion, ELT/ETL, data modeling, storage, APIs, integration, observability, governance, and security), including owning the lakehouse/medallion architecture (bronze/silver/gold) and the data flows that move data across layers at scale.
Translate business and product requirements into pragmatic data designs, data contracts, and architecture roadmaps; create and maintain architecture artefacts (data flow/lineage diagrams, ADRs, reference implementations, modeling guidelines).
Evaluate design options and technology choices, articulate trade-offs, and lead decision-making with stakeholders; push forward the agentic mindset and implementation across the data platform.
Partner with squad leads and senior engineers to design data solutions, break down complex problems, and keep implementations aligned with the target architecture; participate in design/tech reviews to ensure NFRs (performance, scalability, data quality, resilience, security, operability) are addressed early.
Provide hands-on support where it matters most: spike and prototype critical data flows, review complex PRs, and help debug tricky production data and pipeline issues.
Collaborate with Product to shape technical feasibility, sequencing, and scope for data-driven roadmap items; communicate complex technical topics in simple language to non-technical stakeholders.
Define and promote data architecture principles, modeling conventions, coding standards, and reusable patterns (shared transformations, libraries, datasets, services) to reduce duplication and technical debt; drive adoption of shared platform capabilities (observability, CI/CD, orchestration, governance, DevOps tooling) across squads.
Ensure data architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, data quality, and incident response; identify areas of high technical debt or architectural risk and lead remediation initiatives; define and track technical KPIs tied to architecture decisions.
Act as a technical mentor for senior engineers and tech leads, fostering a culture of thoughtful design, documentation, and constructive technical debate; lead by influence- help teams make better decisions instead of making every decision for them.

looking for a Software Architect to lead the technical evolution of our next-generation AI cybersecurity platform. You'll work across teams to solve the company's most challenging architectural problems while remaining deeply hands-on - building prototypes, validating new technologies, and helping engineering teams deliver production-ready solutions. The role requires both deep engineering expertise and the ability to shape the architecture of large-scale data, cloud, and AI systems that power our platform.

What Youll Do
Responsibilities:
Partner with engineering teams to solve complex architectural and technical challenges, leading the design of scalable, secure, and maintainable systems.
Build and validate proofs of concept (PoCs) to evaluate new architectures, data platforms, AI capabilities, and emerging technologies.
Drive technical direction across engineering, product, and data science, turning new technologies into production-ready solutions.
Lead architecture and design reviews, ensuring scalability, reliability, security, and operational excellence.
Mentor engineers through hands-on collaboration, code reviews, and system design discussions while promoting AI-native engineering practices.

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.