דרושים » דאטה » AI Backend Engineering Manager

We are seeking an experienced Backend Team Lead, to build and lead a high-performing backend engineering team while driving critical technical initiatives across our platform. This is a pivotal role where you'll balance hands-on technical contribution with people leadership, shaping both our engineering culture and technical architecture.

You'll own significant parts of our backend infrastructure - from large-scale image processing pipelines and AI model serving systems to distributed cloud architecture and RESTful APIs. As a technical leader, you'll mentor engineers, drive architectural decisions, and ensure our systems scale to handle billions of images while maintaining reliability and performance.

Additionally, you will serve as a Squad Lead, managing a cross-functional business unit that includes both Backend and Frontend engineers, driving end-to-end product delivery.

This role offers the opportunity to directly impact our growth by building the team and systems that power our AI-driven photo editing platform used by professional photographers worldwide.


Responsibilities
Lead, mentor, and grow a team of Backend engineers, conducting 1-on-1s, performance reviews, and career development planning.
Lead a cross-functional squad (Backend + Frontend engineers) as a Squad Lead, driving product initiatives from conception to delivery.
Drive technical strategy and architectural decisions for Backend systems, ensuring scalability, reliability, and maintainability.
Develop and optimize scalable, distributed systems on cloud infrastructure.
Balance hands-on technical work (coding, design reviews, troubleshooting production issues) with team leadership and strategic planning.
Conduct code reviews and establish best coding practices, ensuring adherence to engineering standards across your team.
Monitor system health and lead incident response efforts to ensure high availability of customer-facing services.
Foster a culture of ownership, continuous improvement, and technical excellence within your team.

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

We are looking for an Engineering Manager to lead the evolution of our engineering foundations - across both frontend and backend domains.

This role blends technical leadership, team management, and strategic impact. Youll guide a multidisciplinary team responsible for developer experience, infrastructure, and governance across the R&D organization.

The teams mission is to increase developer velocity, ensure product quality, and strengthen engineering consistency across all our products - from web applications to backend microservices.



What Youll Do

Technical & Strategic Leadership

Define and own the vision and roadmap for Armiss development platform, including web, backend, and AI-enablement initiatives.

Partner with engineering leadership, architects, and product teams to remove friction and increase velocity across R&D.

Establish and govern engineering standards, testing practices, and secure development workflows.

Lead the evolution of our shared frameworks, build systems, and developer tools for scalability and security.

Frontend & Web Infrastructure

Own and evolve the UI development ecosystem, including build systems, testing frameworks, and local development experiences.

Govern our shared UI kit and design system, ensuring consistency, accessibility, and performance across all products.

Partner with UX and product engineers to create a cohesive, maintainable frontend foundation.

Backend & Microservices Infrastructure

Oversee and guide the microservices development framework, templates, and communication patterns.

Optimize monorepo builds, CI/CD pipelines, and runtime standards for efficiency, reliability, and observability.

Implement infrastructure-level protections that improve product quality and prevent regressions.

AI Enablement Across R&D

Champion and integrate AI-assisted development tools (code generation, code review, testing, documentation).

Define patterns and best practices for AI-driven workflows, enabling teams to move faster with higher quality.

Partner with data, DevOps, and product teams to explore how AI can optimize engineering processes and infrastructure.

People & Collaboration

Lead, mentor, and grow a cross-functional team of backend, frontend, and platform engineers.

Foster a culture of technical excellence, innovation, and continuous improvement.

Collaborate closely with Product, UX, Security, and DevOps leaders to align strategy and execution.

We are looking for an experienced SRE Team Lead to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will lead a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 3-4 years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.



What will you do?

Leadership & Team Management

Lead, mentor, and grow a team of SREs, providing technical direction, career development guidance, and day-to-day management.

Own the team roadmap for reliability, observability, and automation initiatives - prioritizing work, removing blockers, and driving delivery.

Conduct regular 1:1s, performance reviews, and hiring processes to build and sustain a high-performing team.

Foster a culture of operational excellence, blameless post-mortems, and continuous improvement.

Act as an escalation point for complex incidents and reliability issues, leading post-incident reviews and ensuring follow-through on action items.


Automation & Infrastructure

Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.

Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.

Drive the adoption of infrastructure-as-code practices across the organization.

Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.


Monitoring & Observability

Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.

Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.

Define and track SLIs, SLOs, and error budgets across key services.

Partner with development teams to embed observability earlier in the software development lifecycle.


Database & Platform Support

Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.

Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.

Your Role:
Team Leader - Integrations Frameworks:
Strategic Vision & Execution: Pioneer and execute a strategy, including necessary tooling, to achieve a 100x acceleration in the integration process.
Technical Leadership & Architecture: Lead the design and development of complex, modular services within the Tenable One platform, ensuring long-term maintainability. Drive high-level architectural discussions, guiding the team toward scalable, cloud-native best practices.
System Reliability & Quality: Champion a "production-first" approach to reliability. Lead root cause analysis for intricate distributed system issues and implement preventative measures to ensure guaranteed system uptime. Collaborate deeply with Product, SRE, QA, and Security teams to deliver technical solutions aligned with business goals.
Team Growth & Mentorship: Recruit, mentor, and lead an exceptional, high-performing engineering team critical to achieving the platform's mission.

As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions.

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions.

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

we are looking for a Director, AI & Machine Learning.
As the Director of AI & ML you will serve as the strategic and technical anchor for our Israel based AI and Machine Learning functions reporting directly to the VP of Data & AI. You will own the delivery of the core capabilities that power our product bridging the gap between high level business strategy and production grade AI execution. This is a high impact leadership role designed for a senior technical partner who can drive cross organizational alignment across Product, Engineering and Platform teams.
We are looking for a leader who moves beyond a traditional management layer to represent the DS/AI function in leadership discussions and strategic planning while maintaining a close operating rhythm with global leadership. In this role you will ensure our AI initiatives are integrated into the heart of the product lifecycle while serving as a credible senior partner for the technical leads. You will be responsible for shaping the future of how our organization builds and scales intelligent systems that handle sensitive healthcare data with precision and scalability.
Scope & Team
This role owns two teams within the Data & AI group:
AI Team: Builds patient-facing AI capabilities, NLP models, and clinical decision-support features.
ML Team: Owns production ML pipelines, model monitoring, and machine learning infrastructure.
Beyond direct team management, this role carries significant cross-organizational strategic responsibility:
Product interface: Bridge the gap between PMs and DS/AI team leads. The TLs are invested at the project level - this Director operates at the strategic level, ensuring AI/ML priorities are shaped early in the product lifecycle, not bolted on after. Be a force of change in how Product and DS/AI collaborate.
Engineering interface: Work peer-to-peer with engineering directors on shared execution dependencies, technical architecture decisions, and resource planning. Own this relationship at the Director level rather than leaving it to individual TLs.
Platform interface: Partner with Platform on infrastructure, data pipelines, and tooling strategy that underpins ML/AI delivery. Ensure DS/AI needs are represented in platform roadmap decisions.