דרושים » הנדסה » AI Architect

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 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

we are seeking a Hands-on Architect to design, build, and evolve the core of next-generation AI cybersecurity platform.This is not an ivory-tower role; it is for a builder at heart. You will write code, build functional prototypes, and own critical services from inception to production. This role demands a unique blend of deep, code-level execution with a broad, system-wide architectural vision that spans our entire data, cloud, and AI stack.
Responsibilities:
Rapidly code and build functional proofs of concept (PoCs) and prototypes to explore and validate new architectures, data platforms, data processing frameworks, and GenAI capabilities.
Validate technical feasibility, scalability, and business impact through working software, not just diagrams or documents.
Partner closely with engineering, product and data science teams to translate emerging technologies into production-ready, scalable systems.
Lead architecture design reviews, proactively identify scalability and performance bottlenecks, and embed security principles into the design process from day one.
Serve as a technical leader and mentor, elevating the team's skills through pair programming, in-depth code reviews, and deep-dive sessions on system design and software craftsmanship.

We are looking for an experienced Software Architect to lead the design and development of our AI-driven software solutions. This role combines deep hands-on architecture with technical leadership, working closely with the CTO to shape system design, guide teams, and align engineering efforts with business goals, with a strong focus on AI-driven capabilities.
Responsibilities
Design and implement software architecture and system structure
Provide technical leadership and architectural guidance to engineering teams
Own the architectural vision and contribute to the technology roadmap
Translate business requirements into scalable technical solutions
Design and evolve AI/GenAI components, including model integration, orchestration and data flow
Guide teams on efficient use of LLMs (latency, cost, scalability)
Evaluate and recommend tools, technologies, and processes
Work closely with the CTO, product, and engineering teams to ensure alignment between architecture and business goals
Ensure quality, scalability, performance, and reliability of the system.

Were looking for a DevOps Architect to help shape the infrastructure strategy behind our Revenue AI platform. This role sits at the center of our engineering ecosystem, driving architectural direction, improving operational excellence, and enabling teams to scale with confidence. Youll work across engineering groups to identify systemic gaps, define scalable standards, and accelerate execution without becoming a delivery bottleneck.
Youll Own:
Infrastructure Strategy & Standards: Define and evolve our cloud and infrastructure architecture across Kubernetes, networking, observability, security, and data platforms. Establish clear standards and scalable best practices that enable teams to move faster with consistency and reliability.
Technical Debt & System Health Visibility: Continuously identify, prioritize, and drive resolution of cross-team technical debt, architectural gaps, and operational inefficiencies. Create organizational visibility around the most critical infrastructure challenges and opportunities.
Cross-Org Technical Leadership: Partner closely with engineering leaders and teams to influence architectural decisions, challenge assumptions, and ensure solutions are scalable, maintainable, and secure. Lead through expertise and influence, not direct ownership.
Developer Enablement & Engineering Velocity: Provide frameworks, tooling direction, and lightweight prototypes or POCs that empower teams to execute independently with higher quality and efficiency.
Critical Infrastructure Initiatives: Drive major cross-functional initiatives around reliability, scalability, security, observability, and cost optimization from identification through execution and measurable impact.
Youll Solve:
Scaling Complexity: How do we maintain simplicity, reliability, and operational clarity while supporting rapid growth and increasingly complex distributed systems.
Cross-Team Alignment: How do we create architectural consistency across independent engineering groups without slowing down innovation and execution?
Operational Excellence at Scale: How do we proactively surface and resolve systemic weaknesses before they become production issues?
Balancing Speed & Sustainability: How do we enable fast delivery today while protecting the long-term health and scalability of the platform?
AI Infrastructure Evolution: How do we build infrastructure that supports modern AI/ML workloads, GPUs, large-scale data pipelines, and future platform requirements
Youll Impact:
Platform Reliability & Scalability: Your work will directly improve the resilience, scalability, and operational maturity of our infrastructure platform.
Engineering Efficiency: By creating better standards, tooling, and architectural guidance, youll act as a force multiplier for engineering teams across the company.
Long-Term System Health: Youll help reduce operational friction, minimize technical debt, and ensure our infrastructure can support long-term business growth.
Execution Quality Across Teams: Your influence will elevate engineering quality, decision-making, and operational discipline throughout the organization.

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

We are looking for a Hands-On Team Lead - Agentic Engineering to lead, build, and actively contribute to a new team focused on applying AI agents, and intelligent workflows to improve business processes across the organization.
This role is both a technical leadership role and a hands-on engineering role. The successful candidate will manage the first Agentic Engineer, help grow the team, and personally contribute to the design, development, integration, and deployment of agentic AI solutions.
The ideal candidate is someone who can lead from the front: writing code, designing architectures, building prototypes, reviewing technical work, solving complex implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI-driven 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.

we are looking for a Data science Team Lead.
As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.
This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.
If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.
What youl do:
Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

we are looking for a Director of AI.
The Director of AI will lead the companys AI organization, including algorithm development teams, embedded algorithm engineers within product squads, and the Data Operations team.
This role combines strategic leadership with execution ownership, driving the development, deployment, and continuous improvement of AI-powered products across power transmission, border security, and critical infrastructure monitoring.
The Director of AI is accountable not only for algorithm innovation, but also for ensuring successful production deployment and measurable customer impact. This leader will establish a customer-first culture across the organization, aligning AI development priorities with customer needs, product objectives, and business outcomes.
The ideal candidate is a visionary yet execution-oriented leader who can bridge cutting-edge AI research with scalable production systems, build high-performing teams, and deliver measurable customer value.
Success in this role will be measured not only by algorithm performance, but by the ability to deliver AI capabilities into production and generate measurable value to our customers.
What Youll Do:
Lead the AI group, including algorithm development teams, embedded algorithm engineers, and data operations.
Build and mentor high-performing teams, fostering a culture of ownership, collaboration, continuous improvement, and customer focus.
Define and execute the AI roadmap in alignment with company strategy, customer needs, and product objectives.
Lead the development and deployment of AI, Machine Learning, Deep Learning, and Signal Processing solutions.
Own the full AI lifecycle, from research and experimentation through production deployment, monitoring, and continuous optimization.
Lead the Data Operations function, ensuring efficient annotation, labeling, and quality processes that support AI development.
Partner closely with Product, Engineering, and business leaders to maximize AI impact across the organization.
Engage with customers and stakeholders to understand challenges, identify opportunities, and drive measurable business value.
Communicate AI strategy, progress, opportunities, and risks to executive leadership.
Contribute to company strategy, product direction, and technology leadership.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.
This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.
The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.
Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.
What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.
Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.
This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help us move faster, automate smarter, and turn ideas into measurable business wins.
What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.