Were looking for an experienced Team Leader who wants to make a foundational impact on the engine that powers cloud security platform.
Our Stack: Python, AWS, Kafka, Redis, SQS, Postgres, Kubernetes. Our scanning surface extends across Azure, GCP, OCI and Alibaba Cloud and others.
What Youll Do:
Lead, mentor and develop a team of senior software engineers through one-on-ones, feedback and technical guidance
Own and drive the delivery of high-impact projects end to end, from design through deployment and production monitoring
Design and review architecture for large-scale distributed systems, with a focus on scalability, resilience and efficiency
Drive the platforms scalability and cost efficiency as scan volumes grow
Collaborate cross-functionally with Product, SRE and other R&D teams to define priorities, interfaces and success metrics
Ensure the reliability, scalability and observability of core services, introducing SLOs and best practices for operations
Uphold the teams engineering standards for code quality, safe rollout of changes and long-term maintainability
Write and review clean, maintainable and tested code

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence - not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating at Amazon scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding , we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention . Our platform runs in production at global enterprise customers, including Fortune 500 companies , delivering mission-critical resilience and sub-second optimization Autonomous execution is a new category, and we are the ones defining it — already running in production inside Fortune 500 environments , where being wrong is not an option. The team is deliberately talent-dense ; every hire changes what we are able to build next. We are looking for a Senior Full Stack Engineer with 7+ years of development experience at leading startups to own Zipher’s entire product surface — the control plane that turns autonomous decisions into something engineering leaders can see, trust, and act on. You will own it end to end: the services and APIs behind it, and the real-time interfaces built on top of them. This is a backend-heavy role: about 70% backend and 30% frontend. It is best suited for candidates whose primary expertise and passion lie in backend development.
What You’ll Do
* Own the product surface end to end : architecture, services, APIs, and the real-time interfaces built on top of them
* Set the technical direction of the control plane — stack, data contracts, and the patterns every engineer after you builds on
* Build high-throughput services that turn live telemetry from production data and AI workloads into decisions, and the explainability layer that makes those decisions readable
* Work directly with the founders on what gets built next, and lead the technical moves that follow — from what enterprise customers need to the architecture that answers it
* Drive quality end to end: testing, CI/CD, observability, and the operational bar for a product Fortune 500 engineering teams run in production
What We Offer A product that is already winning : a new category of autonomous data platform, in production inside Fortune 500 environments A domain of your own : you lead it end to end — the architecture, the stack, and the patterns every engineer after you builds on A seat on the core team : you are one of the engineers deciding what the platform becomes, not one implementing someone else’s decisions Engineering problems that are genuinely hard : real-time telemetry at enterprise scale, distributed decisions, and an explainability layer teams trust in production Engineers worth learning from : a deliberately talent-dense team, direct work with the founders, and a bar that pulls everyone up Room to grow and to lead : your ownership widens as the platform does, and the people who lead moves here keep leading them Top-of-market compensation and a meaningful equity package Ready to own the control plane for an autonomous data platform? Hit Apply.

Were looking for a senior engineer who is ready to move beyond traditional software development and take full ownership of product delivery.

This is not a classic backend engineering role. You will work directly with Product to turn ideas and requirements into production-ready solutions, make the technical decisions, and use AI coding agents as a core part of your engineering workflow.

You will own the outcome, not just the code. AI-generated code is your code, and you are accountable for its quality, security, performance, and maintainability.


What youll do
Own product features end-to-end, from requirements through production and monitoring.
Work with Product to translate business problems into clear technical solutions and execution plans.
Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations.
Use AI coding agents to accelerate implementation, testing, debugging, and automation.
Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability.
Make independent technical decisions and communicate architectural trade-offs clearly.
Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature.
Investigate and solve complex production and performance issues.
Continuously improve how we build, test, and ship software using AI-native development practices.

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

Were looking for an Engineering Tech Lead to help drive some of the most strategic technical initiatives at Unframe. This is not a traditional Tech Lead role. Were looking for someone who is deeply technical and highly hands-on, but also knows how to think strategically, lead architecture decisions, and represent the company in front of enterprise customers and senior stakeholders. Youll work across multiple teams and domains, partnering closely with Platform, Product, and Engineering teams to design and deliver AI-powered enterprise solutions at scale. One moment you might be deep in architecture or code, and the next youll be in a room with customer executives helping guide critical technical decisions. We work on site from our offices in Tel Aviv.
What Youll Do:
Lead architecture and technical direction for strategic enterprise AI initiatives
Work directly with some of the worlds largest enterprises to design and deliver scalable AI-powered solutions
Partner cross-functionally with Platform, Product, and Engineering teams across the company
Stay deeply hands-on with the code and engineering teams
Drive complex technical decisions across scalability, reliability, performance, and system design
Help customers solve real production challenges and build long-term technical trust
Design versatile enterprise-grade solutions across different customer environments and use cases
Influence engineering standards, architecture practices, and long-term technical direction
Operate in a fast-moving, high-ownership environment where execution speed matters

As the Development Team Lead for HiredScore Sourcing Products, you will manage and mentor a cross-functional team of Full-Stack Engineers, Backend Engineers, and QA Automation Specialists.
Your team's core mission will be to translate AI/ML insights into seamless, scalable features that drive efficiency in recruiter workflows-specifically through resurfacing past applicants, prospects, and internal talent. You will own the entire development lifecycle for your products, from core API implementation to deploying user-facing applications and integration layers (web UIs, RPA/workflows, MS Teams bots)
Key Responsibilities:
Lead, mentor, and grow the diverse engineering team, ensuring effective collaboration between backend, full-stack, and QA functions. Drive best practices in development, code quality, and delivery speed.
Design, document, and oversee the implementation of scalable, reliable, and secure systems, ensuring seamless integration between backend AI services and the user-facing product layers.
Ensure the team maintains a strong quality and automation culture by providing strategic direction to QA specialists and upholding high standards for testing and product stability.
Drive development across the full spectrum of product surfaces: APIs (GraphQL/REST), Web Applications (React/Angular/Vue), and specialized engagement layers.
Ensure efficient consumption of AI outputs by downstream systems, particularly through robust queue-based architectures (like RabbitMQ) and workflow automation (RPA).
Partner closely with Product Management, Data Science, and other engineering teams to translate business requirements into technical execution.

We're looking for a Tech Lead Engineer to drive the technical strategy for our cross-platform endpoint agent - built in C#/.NET and hardened for production across macOS, Windows, and Linux. You'll own features end to end across a managed fleet of enterprise devices, stay hands-on writing code, and raise the technical bar for a distributed engineering team. This role also means setting the standard for how the team uses AI coding agents responsibly - fast, but production-grade.

Responsibilities:
Drive the technical strategy for our cross-platform endpoint agent, focusing on C#/.NET core logic while ensuring production readiness across macOS, Windows, and Linux.
Provide technical leadership to a distributed team of engineers, raising technical expertise and engineering practices across the organization.
Own features from discovery to delivery, solving complex domain problems across a managed fleet of enterprise devices.
Maintain a hands-on approach by writing code and mentoring engineers to elevate the organization's technical capabilities.
Architect the agent using C# and platform-specific extensions, ensuring performant integration with each operating system's security frameworks.
Own high-impact technical decisions that balance velocity, security, and reliability.
Deliver maintainable features supported by comprehensive testing, metrics, and monitoring.
Shape the agent roadmap and ensure resilient production systems in collaboration with cross-functional leadership.
Participate in design and code reviews to maintain high engineering standards.
Champion AI-assisted engineering across the team - set the bar for how coding agents accelerate delivery, and establish the practices and guardrails that keep output production-grade.

We're looking for an exceptional, hands-on leader-engineer to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team, operating with a high degree of autonomy in an ambiguous, fast-moving environment.
What You'll Do:
Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset.
Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data.
Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems.
Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams.
Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation.

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.