We are seeking a seasoned Backend Tech Lead with a solid background in high-load environments and experience in managing multiple Linux servers. The ideal candidate is someone who thrives in a fast-paced, innovative, and technology-driven culture.
Responsibilities:
Own architecture for high-scale, user-facing backends and data pipelines.
Lead and mentor engineers; guide design reviews, roadmaps, and execution.
Operate production systems with clear SLOs/SLAs, on-call quality, and blameless postmortems.
Evolve our K8s/GPU platform, CI/CD, and observability to increase deployment velocity and resilience.
Integrate and serve ML models (PyTorch, CUDA/TensorRT, Triton) with a focus on throughput and cost.
Partner cross-functionally (ML, Product, Security, Finance) on priorities and cost/perf trade-offs.
Hire, level up the team, and uplevel engineering standards.

In this role, you will lead a team responsible for building and scaling mission critical backend services that power intelligence platform handling large volumes of data, complex pipelines and high-availability systems. You will combine people leadership with hands-on technical leadership, working closely with product, research and operations to deliver reliable, scalable solutions that directly support the companys growth and business goals.

What Youll Be Doing

Lead and grow a backend engineering team, creating a culture of ownership, quality, and continuous improvement.
Own the design, development, and delivery of backend services, APIs and data pipelines in a cloud-native, microservices-based environment.
Work closely with Product, Research, and Operations to translate business and intelligence needs into scalable technical solutions.
Drive technical and architectural decisions within your domain, balancing performance, reliability, and cost.
Maintain high engineering standards through code reviews, testing, and CI/CD best practices.
Be hands-on in the code (around 50-60%), leading by example.
Take full ownership of your teams roadmap, delivery, and technical health.
Technology stack includes: C#, NestJS, Kubernetes, Kafka, and various relational and non-relational databases, Elasticsearch.

Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
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.
The Dream-Maker 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.

Required AI Engineering Team Lead
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions - customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
As the AI Team Lead, you will guide a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll combine technical depth with leadership skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Leadership & Team Management:
Lead, mentor, and grow a team of machine learning engineers and data scientists.
Foster a culture of technical excellence, collaboration, and continuous learning.
Define team goals, measure progress, and ensure high-quality deliverables.
Strategy & Roadmap:
Own the data science strategy and align it with company objectives.
Identify opportunities for applying machine learning and generative AI across products and internal systems.
Evaluate emerging technologies, tools, and methodologies to keep the team ahead of the curve.
Hands-On Technical Work;
Design, prototype, and implement ML models, including LLM-powered copilots, retrieval systems, and fraud detection pipelines.
Guide the deployment of models into production environments with scalability and reliability in mind.
Ensure best practices for experimentation, evaluation, and monitoring.
Cross-Functional Collaboration:
Work closely with engineering to integrate ML components into production systems.
Partner with product managers to align solutions with customer needs and business priorities.
Collaborate with security and compliance teams to ensure ethical and secure use of data.

We are establishing a new backend group that will take full ownership of a core application area.
We are looking for a Senior Backend Developer who will lead the backend effort end-to-end - from initial architecture and technology choices, through implementation and scaling, and into long-term ownership and evolution.
This is a hands-on technical leadership role. You will design, build, and own production systems, work closely with multiple teams, influence product direction, and set the technical bar for the group.
We embrace an agile mindset - you should be comfortable with context switching, handling multiple priorities, and adapting quickly to changing requirements.
Responsibilities
Take full ownership of the backend architecture for a major application area
Design and implement scalable, reliable, and maintainable backend systems
Lead technical design and decision-making, including technology and architecture choices
Work closely with product, frontend, platform, and other backend teams
Participate in product vision discussions, brainstorming, and planning sessions
Translate product requirements into robust technical solutions
Write high-quality, production-grade code
Drive debugging and root-cause analysis of complex production issues
Ensure best practices in performance, reliability, security, and observability
Mentor and technically guide other backend engineers as the group grows.

We are looking for an experienced Backend Team Lead to join our Harmony SaaS Security group and lead the development of our Data Loss Prevention (DLP) platform.
Job Id: 25362
Our team was born from a successful cybersecurity startup acquisition and operates with a startup mindset inside a global cybersecurity leader. We focus on building advanced security solutions that protect organizations from sensitive data exposure across modern SaaS environments.
As a Backend Team Lead, you will own the architecture and evolution of a large scale DLP platform responsible for detecting, analyzing, and protecting sensitive data across thousands of organizations and millions of SaaS events.
You will lead a team of highly skilled backend engineers, working with a modern cloud native stack including Go, GCP, Kubernetes, Kafka, and Postgres, and will design systems that process and analyze massive volumes of security data in real time.
This role combines technical leadership, system architecture, and hands-on development, with opportunities to shape the future of our platform, introduce AI-driven security capabilities, and drive engineering excellence across the team.
If you enjoy building large scale distributed systems, leading strong engineers, and solving complex security problems, we would love to meet you.
Key Responsibilities
Lead and grow a team of backend engineers, fostering a culture of ownership, innovation, and engineering excellence.
Own the technical direction and architecture of the DLP product and its backend services.
Design and build high scale distributed systems that ingest, process, and analyze large volumes of SaaS security events.
Drive architectural decisions around event driven systems, data pipelines, and cloud native infrastructure.
Collaborate closely with product managers, security researchers, and data teams to deliver impactful security capabilities.
Mentor engineers through technical guidance, architecture discussions, and code reviews.
Ensure high standards for performance, reliability, scalability, and observability.
Build and optimize systems leveraging technologies such as Kafka, Kubernetes, and GCP services.
Drive innovation by exploring and integrating AI-based capabilities for advanced data classification and security detection.
Maintain operational ownership of production systems, including monitoring, troubleshooting, and continuous improvements.

We are looking for a technically-oriented Engineering Team Lead to lead a high-performing team focused on detection and analytics. This is ideal for someone who is passionate about people leadership but doesnt want to walk away from the code entirely. You will balance roughly leadership/management with hands-on technical contribution, ensuring our microservices architecture remains robust and scalable on Google Cloud.
Key Responsibilities
Drive Execution & Delivery: Take full ownership of your team's software development life cycle. You will manage sprint planning, ensure high-velocity execution, and deliver critical features on time in a fast-paced Agile environment.
Lead & Empower: Directly manage, mentor, and grow a team of talented backend engineers. You will conduct 1-on-1s, guide career development, and foster a culture of continuous learning and high performance.
Shape the Architecture: Act as a technical sounding board for your team. You will guide technical design discussions, review architectures, and ensure our systems remain scalable, secure, and resilient under massive loads.
Collaborate Across Teams: Partner closely with Product Managers, DevOps, UX designers, and Security Researchers to align engineering efforts with our strategic roadmap and customer needs.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI , covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 3-4 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.

We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Health.

Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

Who are you?
You are a seasoned backend or data engineer with experience working on production-grade ML/AI-powered products. You thrive in fast-paced, high-ownership environments and are passionate about building scalable and reliable systems. You understand the unique requirements of delivering AI/ML features in production, and you are comfortable working with modern technologies in the LLM/RAG ecosystem.
You pride yourself on delivering high-quality solutions quickly, without sacrificing design or reliability. Youre known for your responsiveness, collaborative spirit, and service-oriented mindset-especially when youre on-call and the stakes are high.How will you contribute?
Design, implement, and maintain scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.
Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all our Health products.
Monitor and improve uptime, reliability, and observability of our data infrastructure and pipelines.
Build and maintain systems to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.
Work closely with product and engineering teams to deliver new features rapidly and with a high standard of technical excellence.
Drive innovation in how we build, measure, and optimize data features, backend services, and AI product integrations.
Participate in on-call rotations with a service-oriented approach and fast responsiveness.
Lead scalability efforts to support increasing data volumes, expanding AI/ML initiatives, and new product launches.

Were hiring a ML Engineer to accelerate AI-driven innovation across our B2B SaaS platform.

Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.

What You Will Do:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across our product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.