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We are a young, dynamic hi-tech company seeking a passionate, resilient, and proactive Technical Support Engineer to join our growing team.
In this role, you will become an expert in the inner workings of our platform and take responsibility for Tier-1 support, cross-team investigations, and customer success enablement. You will work closely with Product, Engineering, and Business teams to ensure a smooth client experience, providing guidance, issue resolution, proactive support, and intiatiives to improve the team's performance
This is a demanding and fast-paced role ideal for someone who thrives under pressure, has deep empathy for users, and is excited about solving problems and helping others succeed.
Responsibilities:
Serve as the first point of contact for Tier-1 technical support, handling and triaging issues through Zendesk and collaborating as needed across departments.
Investigate root causes, debug issues, and coordinate escalations with engineering and product teams.
Guide customers through platform features, API integrations, and SFTP connections.
Help define and improve internal workflows by creating documentation, process diagrams, and training materials.
Reproduce and debug customer-reported problems, escalating appropriately and following up for timely resolution.
Conduct deep investigations into technical issues and ensure accurate handoff to relevant teams.
Provide product education and support to clients, helping them understand platform functionality.
Being on call for urgent issues as part of a regular rotation.

Were looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows.

You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making our ML reliable, fast, cost-efficient, and production-ready.

This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up.

What Youll Do
Build & Scale ML Pipelines
Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments.
Establish LLM-Focused CI/CD
Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment.
Optimize Runtime & Inference
Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability.
Own ML Infrastructure
Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
Operational Excellence
Monitor and optimize production models for performance, cost efficiency, availability, and observability.

Required Technical Support Engineer Tier 3
As a Technical Support Engineer on our Tier 3 team, you'll work with some of the most advanced companies leveraging cutting-edge AI-driven systems to enhance business performance. Your role involves deep technical investigation, resolution of complex issues escalated by the Support team, and acting as the main technical liaison with R&D. You'll play a critical role in identifying recurring issues and driving continuous improvement initiatives in collaboration with R&D and Product Management through leveraging customer feedback and data across the Support team.
Youll Own:
Subject Matter Expertise: Serving as a dedicated subject matter expert (SME) for a specific product area and owning it end-to-end.
Escalation Management: Partnering with Tier 2 Support and Customer Success teams to prioritize escalations, communicate updates, and drive end-to-end resolution processes.
Team Enablement: Educating and upskilling Tier 2 teams by sharing insights, documenting learnings, and delivering trainings to bridge knowledge gaps and improve first-line resolution rates.
Support Tooling: Identifying gaps and advocating for, or creating troubleshooting tooling as needed, to better equip Support team members in identifying root causes faster and delivering more holistic resolutions as early as possible.
Youll Solve:
Complex Troubleshooting: Performing root cause analysis, troubleshooting, and resolving issues using a variety of tools, datasets, and cross-functional collaboration.
Recurring Technical Challenges: Aligning closely with R&D teams to communicate recurring technical themes and suggesting improvements.
Customer Obstacles: Reading and understanding code and writing occasional scripts to resolve complex customer issues.
Youll Impact:
Product Quality & Supportability: Collaborating with R&D and Product Management to provide solutions and workarounds, and to implement product features or support tools that ultimately reduce the need for customers to submit tickets.
Support Team Proficiency: Mentoring and enabling support teams to improve technical proficiency and resolution capabilities.

Security teams are not short on tools. They are short on time, alignment, and the ability to actually close exposure. That's why most breaches could have been prevented with a tool that was already in use.
our company was built to change that.
We are the first Agentic Exposure Ops Platform, designed to prevent the preventable breach by turning fragmented signals into coordinated action. Our agents investigate risk, drive remediation, and verify that issues stay closed, continuously, without adding overhead.
we are helping organizations move from reactive workflows to continuous execution, replacing manual effort with systems that actually move the work forward.
At our company, engineering isn't a service function it's where product happens. We're looking for a Fullstack (Product) Engineer who lives at the intersection of craft and product sense:You care as much about why we're building something as how it feels in the user's hands. You're an engineer who connects naturally with other engineers, and who enjoys mentoring and ramping up the people around you.
You'll own experiences end-to-end from the first PRD conversation to the KPI dashboard weeks after ship. You'll shape our component library, raise the bar on our frontend infra, and help define what "good" looks like across the R&D org. This isn't a role where you get handed pixel-perfect mocks and a closed ticket. You'll have opinions, and we'll want to hear them.
What you'll do
Craft the experience. Design and build polished, performant UI in Vue 3 (Composition API) from the tiny interaction details to the data layer behind them.
Own the full journey of a feature. Partner with Product on the PRD, define the KPIs that actually matter, ship it, then track whether it moved the needle and iterate honestly if it didn't.
Shape the component library. Evolve our patterns, primitives, and the infra that lets the whole team build faster without sacrificing quality or consistency.
Go full-stack when it counts. Write Node (NestJS) services and work across our data stack (Postgres, Snowflake, ClickHouse) to deliver features truly end-to-end.
Push AI-assisted development forward. Build the guardrails, skills, and workflows that let engineers contribute code quickly and safely you'll help make AI a force multiplier for the whole team, not a liability.
Raise the bar org-wide. Your taste in UX, and code quality should ripple well beyond your own team.

We are looking for a Head of Forward Deployed Engineering to lead the team that turns our platform into live production systems inside the largest enterprises. You will own a team of 10+ FDEs (and growing), the delivery bar they are held to, and the outcomes they ship.
This is a player-coach role. You set the standard, build the system that enforces it, and stay close enough to the work to review a flow design and call out what's wrong.
What You'll Do
Own delivery outcomes. On-time go-lives, production stability and client satisfaction all land on your desk. You manage by data: delivery metrics, quality signals, escalation rates and client feedback.
Raise the bar. Run a clear performance system with a defined FDE bar, 30-60-90 ramps for new hires, and honest evaluations. Coach the people who can grow. Make the hard calls on those who can't.
Run the operating rhythm. Own the flow review forum, the deployment status cadence, and the on-site schedule across clients.
Grow the team. Own the hiring pipe, from sourcing through a practical interview loop to onboarding that gets new FDEs to independent delivery in 90 days.
Stay in the field. Show up at key clients, especially around go-lives. Your credibility comes from being in the room, not above it.

our company builds the production-grade AI backbone for top-tier enterprises. We don't just wrap LLMs. Our platform autonomously handles mission-critical workflows, replacing operational friction with seamless, predictive experiences. We are a lean, engineering-driven company working directly with the biggest players in the market.
An FDE at our company is a customer-embedded engineer who owns the technical success of an AI deployment end to end. You don't advise and hand implementation to someone else. You are the implementation owner. You take an ambiguous business problem, break it into solvable technical components, build the solution on our platform, and stay with it until it works reliably in production.
What You'll Do
Own deployments end-to-end. From signed deal to production go-live and stabilization. No hand-offs.
Build production AI agents. Design and ship agent flows on our platform: prompt engineering, orchestration, edge cases, and the testing discipline that makes them production-grade.
Integrate into brownfield reality. Legacy systems, APIs, CRMs, telephony and customer infrastructure, while navigating security, compliance and incomplete requirements.
Debug in environments you don't control. When production misbehaves inside the customer's stack, you find it and fix it.
Push back with judgment. Challenge poor requirements, find creative alternatives, and align technical and business stakeholders behind them.
Be embedded with customers. On-site several days a week during active deployments, often as the most senior technical person in the room. On-site days carry dedicated compensation on top of your salary, and every production go-live carries a milestone bonus.

Were looking for a Devops Engineer to join our core team and build the engine behind AI-native security. We aren't just building another dashboard, we are architecting a system that processes massive data streams and pushes AI models to their absolute limits to outthink modern attackers. If you are a builder at heart who thrives on high-scale challenges, ownership, and the fast pace of an early-stage startup, youll fit right in.
What You'll Do
Build and maintain our cloud infrastructure across multiple environments
Design CI/CD pipelines that let the team ship fast without breaking things
Implement security best practices at every layer of our stack
Create monitoring, alerting, and observability systems
Automate everything that can be automated.

We are looking for a Software Engineer to join our Core Team. This team owns and evolves our core query and indexing infrastructure, working directly on our query engine, query optimizations, indexing engines and pipeline. Youll solve deep technical problems and help shape the architecture of high-performance, complex systems.

WHAT YOU WILL DO
Design, develop, and maintain connectors to Databases and SIEMs.
Add new indexing capabilities to our indexing pipeline.
Own technical decisions end-to-end from design to production rollout.
Collaborate closely with product, infra, and data teams to align on technical direction and integration.

We're looking for a Software Engineer to join our R&D team. In this role, you'll design and build scalable, high-performance systems that bring together rich backend capabilities and intuitive frontend experiences. You'll be part of a mission-driven team, building innovative technologies that enable security teams to detect, analyze, and respond to threats faster than ever before.


WHAT YOU WILL DO
Develop and own end-to-end features across the entire stack, from backend services to frontend interfaces.
Design and implement distributed backend systems that handle massive volumes of security data in real-time.
Build modern, responsive, and accessible user interfaces using React, TypeScript, Remix, Tailwind, and Shadcn.
Architect and maintain robust APIs and data contracts between the frontend and backend.
Collaborate with product, design, and security experts to deliver impactful user facing features.
Ensure high code quality by writing comprehensive unit, integration, and E2E tests using tools like Vitest, Playwright, and React Testing Library, as well as backend testing tools
Optimize system performance, reliability, and scalability on both ends of the stack.
Take part in critical architectural discussions and influence the technical direction of the platform.

We're looking for an AI Engineer to join our team. As an AI Engineer, youll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO
Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

The NPI Engineer will be responsible for representing Operations/Engineering and new projects and transfer products to production including the following:

OPS Project manager for New Product Introduction cross functional, following Align PLCM.
Responsible for building Product/Production file, Product documentation, BOM, jigs/tools/Fixtures design
Responsible from moving from prototype to mass production
Responsible of Design transfer process during the PLC stages.

Key Responsibilities


In this role, you will

Be responsible for the transfer of a new products from development to production.
Support International supplier and turnkey management during PLC stages
Leading Engineering changes as the prime interface in order to introduce necessary engineering/R&D changes while understanding the implications in Logistic, Testing and Production; End to end.
Writing and executing validations and writing testing requirements.
Leading FAI process to new products and responsible for the supplier quality
Involvement during design phase in connection with DFXs (Assembly process, Manufacturability etc).
Define the documentations needed in order to manufacture the products correctly (Test procedure, Assembly instruction etc)
Define and design jigs, tools and fixture to allow repetitive and robust manufacturing with mass production orientation.
Construct and maintain complex Bills of Materials (BOM) in PLM system.
Perform production line Training and accompany Prototype and NPI assembly, dry run.
Work in cross functional teams with RA, Quality and SC etc.
Investigating RCAs

We are seeking a Product Engineer to support products throughout their lifecycle, from New Product Introduction (NPI) to mass production and sustaining activities. In this role, you will work closely with R&D, Manufacturing, Quality, Supply Chain, and Operations to ensure products are reliable, manufacturable, cost-effective, and compliant with quality standards.

Key Responsibilities
Support products through NPI, production ramp-up, and sustaining engineering activities.
Lead technical investigations, aid Jigs design for manufacturing, root cause analysis, and implementation of corrective actions.
Drive Engineering Change Orders (ECOs/ECRs) and assess impact on manufacturing and supply chain.
Provide engineering support to manufacturing and resolve complex technical issues.
Manage product documentation, BOMs, and configurations in PLM/ERP systems.
Lead validation and qualification activities related to product and process changes.
Support suppliers and contract manufacturers to resolve technical challenges.
Identify opportunities for cost reduction, yield improvement, and process optimization.

Were looking for a Core Full-Stack Engineer who combines strong product instincts, deep engineering skills, and the ability to move fast without compromising on execution quality.
Youll be a primary technical driver, taking significant product modules from concept through design, architecture, implementation, and production. You wont just implement finished specifications, youll partner with product and design to shape the solution, make technical decisions, and own delivery across the entire stack.
Your work will turn complex, large-scale data into fast, intuitive products for Fortune 500 marketing teams. Youll build across the entire data and application stack-from data ingestion and ETL pipelines to scalable backend services, polished interfaces, and responsive visualizations. This role combines full-stack development with hands-on data engineering, owning how data is collected, transformed, stored, and served to make exploring datasets with billions of records feel effortless.
This is a hands-on role for someone who has driven meaningful product development in a fast-growing startup and is comfortable taking ownership before every requirement has been defined.
Responsibilities
Own complete product modules from concept to production.
Build and own production data pipelines.
Design scalable data models and APIs.
Build fast, polished, data-intensive interfaces.
Drive performance across the entire stack.
Ensure data quality and reliability.
Create reusable product foundations.
Own production reliability and safe delivery.
Lead through hands-on execution.

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.