דרושים » הנדסה » Staff AI Platform Engineer

We're looking for an AI Engineer who is equal parts builder, enabler, and visionary.
This is a rare opportunity to join a small, elite team at the ground floor and have outsized impact on how AI is designed, built, and shipped across a globally recognized cybersecurity platform.
If you thrive at the intersection of cutting-edge AI research and real-world production systems and you want your fingerprints on something that matters - read on.
Why Join Us?
Greenfield opportunity - you're not joining a mature team with fixed patterns, you're helping define them.
Real impact at scale - your work will influence products used by thousands of organizations worldwide.
A team of great people - small, senior, and genuinely collaborative.
Freedom to innovate - we encourage bold ideas, fast experiments, and honest feedback.
our company's AI moment - AI is a company-wide strategic priority, and this group is at the center of it.
*we are an equal opportunity employer committed to diversity and inclusion.
Key Responsibilities
What You'll Do:
Build AI infrastructure - Design and develop the foundational tools, frameworks, and pipelines that power the group's AI capabilities, with a focus on LLMs and Generative AI.
Enable AI across the team - Act as the group's AI enablement engine: establish best practices, create internal tooling, and uplift teammates to work effectively with AI systems.
Own AI agents & agentic workflows - Design, implement, and iterate on autonomous agents and multi-step AI pipelines integrated with a variety of tools and environments.
Bring AI to production - Take models and capabilities from prototype to production-grade systems - reliable, scalable, and observable.
Shape the big picture - Contribute to the group's AI strategy, not just its execution. We want someone who asks "why" before diving into "how."
Stay ahead of the curve - Continuously research and evaluate emerging AI techniques, models, and tools - and bring what's relevant back to the team.
Collaborate and communicate - Write clearly. Think clearly. Work closely with researchers, engineers, and product stakeholders to align on goals and drive outcomes.

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

The Prisma Browser group is building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
Prisma Browser is an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.

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.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
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 building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
we are an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.
Qualifications
Your Impact
Design and implement automated evaluation loops, static analysis, and rigorous quality gates to ensure the ADLC process doesn't just write code, but consistently produces great, production-ready code.
Help the team tackle complex, hard problems to elevate our autonomous development product from "good" to "excellent".
Lead complex initiatives in Context Engineering and Prompt Engineering.
Manage and orchestrate the complex ecosystem of autonomous agents utilized for internal development.
Serve as a leading individual in a very strong team professionally and personally - Were looking for someone who not only delivers his own work but improves that of those around them.
Find space for growth to push the entire team or group forward - New projects, changing processes or improving existing tools.
View prompt engineering as a core engineering discipline-where rewriting agent behavior is a versioned, reviewed, and tested code change.
Act with a debugging temperament; conduct deep-dive analyses of raw agent transcripts to diagnose non-deterministic failures and ascertain root causes instead of merely working around them.

we are building the future of AI Security - a platform that enables organizations to adopt AI boldly while keeping it governed, observable, and secure.
Were looking for a hands-on Software Engineering Team Lead to own our AI Security product for coding agents - from Claude Code, Codex, and GitHub Copilot to cloud-native coding environments and fully autonomous development agents.
This is a high-impact, product-driven leadership role at the intersection of AI, developer experience, cloud infrastructure, and enterprise security. Youll lead a full-stack team that owns this domain end-to-end: from infrastructure and policy engines to delightful product experiences that engineering teams actually love using.
What Youll Do
Lead and grow a full-stack engineering team dedicated to securing AI coding agents and autonomous development workflows.
Own the entire product area - strategy, architecture, roadmap execution, quality, customer adoption, and continuous iteration.
Design and build production-grade capabilities spanning AWS & Kubernetes infrastructure, backend services, real-time policy & enforcement engines, rich APIs/integrations, and intuitive UI/UX.
Partner closely with Product, Design, Sales Engineering, and customers to stay ahead of emerging AI risks and developer needs.
Set a high bar for engineering quality, ownership mindset, fast delivery, and product thinking across the team.
Help shape how the industry solves one of the biggest challenges of our time: letting AI agents move at incredible speed without compromising security or governance.

MA?LYS is a fast-growing global body care brand, built on a proprietary e-commerce platform, deep consumer insights, and a relentless focus on performance. Millions of women worldwide use our products, and we are on a mission to become one of the most influential body care brands globally.
We operate at extreme velocity, with high standards and an obsession with results. We believe in challenging conventional thinking, making data-driven decisions, and moving quickly from idea to execution.
We are looking for a Head of AI to build and lead MA?LYS' AI transformation journey, serving as a rare opportunity for a highly strategic and deeply hands-on builder who thrives at the intersection of business, technology, and execution. In this role, you will have the ultimate playground to shape how our entire company operates, influence every major function, and create a lasting competitive advantage for a leading body care brand. Initially operating as an individual contributor partnering closely with the CEO and the Management Team. Over time, you will transition to build and lead a small, high-performing team as AI becomes an increasingly critical capability across our global e-commerce and retail operations.
To thrive in our high-pace environment, you must think like an owner, not a consultant, and be equally comfortable discussing macro business strategy with executives as well as writing code to solve a messy problem yourself. You are someone who embraces ambiguity, enjoys building from scratch, and is completely obsessed with execution. You possess the high emotional intelligence and empathy required to collaborate with non-technical stakeholders and build trust, yet you maintain the thick skin, resilience, and great sense of humor needed to handle direct communication and rapid structural pivots. Most importantly, you maintain an uncompromising commitment to quality and process improvement, ensuring that every automation or workflow you deploy actively drives our core business metrics forward without requiring hand-holding or constant reminders.
Your life at MA?LYS will look like…
* Define and lead the company's AI strategy and execution roadmap.
* Identify the highest-impact opportunities for AI across all business functions.
* Prioritize initiatives based on measurable business value, speed of implementation, and scalability.
* Design, build, deploy, and continuously improve AI-powered workflows, tools, automations, and agents.
* Translate business challenges into practical AI solutions that improve performance, efficiency, and decision-making.
* Develop production-ready applications and workflows using modern AI technologies, APIs, agents, and automation frameworks.
* Drive adoption and behavioral change across teams.
* Partner directly with business leaders to identify opportunities and implement solutions.
* Evaluate emerging technologies, models, vendors, and platforms.
* Establish governance, standards, architecture, and best practices for AI development.
* Define and track success metrics for every AI initiative, ensuring measurable impact on growth, productivity, speed, efficiency, or cost.
You will thrive in this role if you have…
* Strong technical foundation in Computer Science, Software Engineering, Data Science, or a related field.
* 5+ years of experience building technology, data, AI, automation, or software solutions in high-performance environments.
* Proven experience identifying business opportunities and translating them into deployed AI products, agents, automations, or workflows that drive measurable business impact.
* Hands-on experience working with modern generative AI technologies, LLMs, agent frameworks, APIs, embeddings, automation platforms, and production deployments.
* Strong proficiency in Python, SQL, APIs, and data-driven application development.
* Deep understanding of business operations, growth metrics, p

Required Senior AI Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the agentic AI platform that turns LLMs into reliable, production-grade capabilities. You care about clean APIs, well-defined service boundaries, and systems that teams can build on with confidence. We are AI-first across the board - every team builds and operates agents. You'll architect and ship the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation pipelines, tool-calling infrastructure, and retrieval systems. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments.
If you want to make a meaningful impact, join our mission and build the agentic AI platform that drives Sovereign AI products - this role is for you.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

we are building the technical layer that brings AI-native code quality into real engineering workflows. As our partnership ecosystem grows, were looking for a principal-level engineer to turn strategic integrations into shipped products.
In this role, youll be a technical visionary and builder. You will design and implement the next generation of Model Context Protocol (MCP) servers, APIs, and platform integrations for key strategic partners like cloud providers, Anthropic, Cursor, and OpenAI. This is a high-leverage role where your expertise will directly shape how our company- the missing quality-focused system-plugs into the complex, autonomous, multi-agent development environments of tomorrow.
Ideal for someone who thinks deeply about developer experience, moves fast, and enjoys building technical infrastructure that scales through partnerships.
Mission: Make our companyunavoidable across the Agentic SDLC. Own the integration playbook that brings our company into every critical developer surface - IDEs, repos, CI/CD, code review, cloud platforms, and the AI agents shaping how software gets built. Build the technical layer that turns our company into the default quality, governance, and trust gate across the SDLC, translating cutting-edge research into integrations that scale, ship, and become embedded in how teams work.
Responsibilities
Wrap our companys capabilities as a public, composable surface. Turn our company Review, Aware, and Skills into clean, documented building blocks that any partners engineering team can adopt without hand-holding. Treat the public API, SDK, and MCP surface as a product - versioned, stable, well-documented, and obsessively focused on DX.
Be the engineering counterpart on partner conversations. Sit shoulder-to-shoulder with the Product Partnerships Lead in partner discussions. Translate ambiguous we want to integrate conversations into concrete technical scopes, integration paths (MCP vs. SDK vs. API), and shipping timelines. Be credible enough that a partners principal engineer takes the conversation seriously the first time.
Ship marketplace and cloud integrations. Own the technical execution behind cloud marketplace launches (AWS, Azure, GCP) - deployment artifacts, SaaS metering, private offer plumbing - so the commercial motion is never bottlenecked by engineering.
Define the integration playbook. Make the path from new partner interested to integration live repeatable. Document the patterns, build the reusable primitives, and reduce the per-partner engineering cost over time so the team can scale partnership volume without scaling headcount linearly.
Hold the DX bar across every partner-facing surface. Docs that work the first time. SDKs that dont surprise. Errors that explain themselves. Examples that run. If a partners engineer cant get to hello world