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Required AI Platform Engineering Team Lead - Sovereign AI Engineering
We're building AI that nations own and control, deployed where almost no one else can operate. ingesting and structuring complex data, and driving practical actions that can literally impact the lives of billions of people around the world. This role helps make that real.
The Dream Job:
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. 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. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
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're looking for an Engineering Group Manager to lead this group. Reporting to the VP of R&D, you'll own the engineering execution, architecture, and technical direction of the products that define what Optibus is. You'll lead a group of full-stack team leads and engineers building large-scale, complex SaaS products on a cloud-native platform, working closely with our Algorithms group.

This is not a 2024 group manager role. We are not hiring someone whose day is meetings, status reports, and approvals. We are hiring a hands-on technical leader who codes, designs systems, drives architecture, leverages AI as a force multiplier, and is measured by impact rather than headcount.

What You'll Own

R&D leadership partnership. You're a key member of the R&D leadership team, actively shaping departmental strategy and driving high-level decisions across the organization - not just running your own group.
The core of the product. Engineering ownership of Planning, Scheduling, and Rostering - the products at the center of the platform, used by transit agencies and operators worldwide.
Architecture and technical direction. You set the technical bar. You participate in design, review architecture, write PRDs, and dive into code reviews when it matters. The hardest problems land on your desk.
A group of team leads and engineers. You'll mentor team leads, grow engineers, and build a small, sharp, high-leverage organization rather than a large one.
Delivery, quality, and velocity. You drive the engineering processes that ship a high-quality product on production-grade SaaS - fast, with low defect rates, and with continuous improvement.
AI-native engineering. You leverage AI agents and automation to multiply the output of your group - both in how the team builds software and in what we build into the product.
Cross-functional partnership. Tight collaboration with Product, Design, Algorithms, and Customer-facing teams to translate complex transit-domain needs into shipping software.

As a Software Development Team Leader Youll lead a team of strong engineers building the core platform behind one of the largest real-time recommendation systems in the world, with full ownership from design to production and the freedom to move fast and solve complex infrastructure challenges.1.4 billion users. 950,000 requests per second. 140TB of fresh data every day. 800M metrics every minute (for monitoring). Thats the scale our companys Production Engineering team operates at - and were looking for a Software Development Team Leader to help drive what comes next.

We're looking for a Platform Team Leader to own the foundational systems that power R&D organization. The Platform team is a horizontal, internal-facing team - its customers are the engineers, data scientists, and analysts on our application teams, and its mission is to make them faster, safer, and more productive.
You will lead a team responsible for our production-critical data ingestion (scraping system, data normalization platform), our developer experience surface (Python mono repo, packages and services framework, CI/CD, shared images), our Airflow base layer, and our backoffice. These systems sit on the critical path for production - every other team depends on them, and uptime, incident response, and reliability are core to the role.
This role is for a hands-on technical leader who enjoys both shipping code and growing engineers. You'll spend roughly 50% of your time hands-on writing code, reviewing designs, and the rest leading the team, partnering with peer team leads, and shaping the technical direction of our platform with the VP R&D and CTO.
Responsibilities
Lead and grow a team of strong backend engineers, owning hiring, mentorship, performance, and personal growth
Own the team's roadmap end-to-end: scoping, prioritization, delivery, and quality
Drive the architecture and evolution of the platform layers your team owns - both the data plumbing that feeds and the developer-experience surface other R&D teams build on
Contribute hands-on (~50%) to design, code, code reviews, and production debugging
Set and uphold engineering standards across the team - code quality, system design, testing, observability, and operational excellence
Partner closely with peer team leads and the VP R&D to align on shared infrastructure, ownership boundaries, and developer experience
Lead by example on production incidents and customer-impacting issues
Influence broader R&D direction as a member of the R&D leadership forum

Required Engineering Team Lead - Application Infrastructure
Tel Aviv
As an Application Infrastructure Team Lead, youll spearhead the development of the core frameworks and services that power our entire ecosystem. In this role, youll sit at the vital intersection of application development and systems engineering, ensuring our platform remains resilient, high-performing, and developer-friendly as we scale.
If you are a technical heavyweight who loves Java but thrives on leading teams through complex data and infrastructure puzzles, this is your opportunity to build the foundation for our next phase of growth.
Youll Own:
Team leadership & mentorship: Guiding a high-performing engineering team and fostering a culture of ownership and excellence.
Core application infrastructure: Designing and maintaining mission-critical frameworks using Java and Spring Boot.
Technical standards: Defining and enforcing the benchmarks for code quality, system performance, and security across the entire stack.
Streaming & messaging pipelines: Owning the reliability and scalability of asynchronous communication using Kafka or SQS.
Youll Solve:
Data layer optimization: Leading specialists to tackle challenges in high availability and performance across PostgreSQL, MongoDB, OpenSearch, and Redis.
Distributed systems complexity: Designing robust pipelines for asynchronous communication and data streaming at scale.
Architecture gaps: Bridging the gap between DevOps and Product teams to align infrastructure capabilities with evolving business needs.
Youll Impact:
Engineering velocity: Providing the foundational building blocks that empower all product engineering teams to build faster and better.
System reliability: Ensuring the high availability, scalability, and security of mission-critical systems.
Technical culture: Driving a mindset of continuous improvement and technical excellence that resonates across the R&D organization.

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.
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're looking for a Senior Data Infrastructure Engineer to help us build the data foundation that powers everything does. You'll be joining the Data Platform team in TLV, working on the infrastructure that ingests, processes, and governs data across a growing stack of products, customers, and microservices - structured and unstructured, streaming and batch. The work you do here sits at the core of how every team makes decisions.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Design and implement data solutions for all application requirements in a distributed microservices environment
Build ingestion layers and a data lake using streaming ETLs and Change Data Capture
Implement large-scale batch and streaming pipelines with modern data processing frameworks
Build pipelines and scheduling infrastructures that other teams rely on every day
Ensure data quality, compliance, and governance across entire data platform
Help shape data-mesh concepts that empower other teams to leverage data independently
Partner with Data Engineers, ML Engineers, Data Scientists, BI Engineers, and Product Managers to move fast and build right

Grip Security is looking for a Senior Data Platform Engineer to join our community!
We are a fast-growing startup in the software-as-a-service and AI Security Industry. We provide innovative solutions to securing the whole organization-to-SaaS surface. (More details: https://grip.security)
Using the newest technologies, we're working on solving a huge problem all enterprises face today - to govern the accessibility of all their employees to all 3rd party vendors (GitHub, SendGrid, Atlassian, and thousands more!), and ensure there is no leftover/unwanted access to any of the organization's SaaS and AI assets. The SaaS and AI security field is complex and challenging; therefore, we're looking for super-talented people, who are not afraid of technical challenges and breaking down barriers to achieve good solutions.
The job
As a Senior Data Platform Engineer, you will play a key role in building and evolving Grips modern data platform - the infrastructure that powers product features and analytics across the company.
You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.
Responsibilities:
Design, build and operate a cloud-native modern data platform.
Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
Improve developer experience and platform usability through tooling and automation.
Lead and support large-scale data migrations and architectural improvements.
Drive best practices around infrastructure, CI/CD, testing, and system design.
Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.