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As a QA Automation Tech Lead, you will drive automation strategy and testing frameworks. Youll take end-to-end ownership of the automation architecture across all testing layers (API, UI, and E2E), from design to CI/CD integration. Youll collaborate closely with R&D and Product, serving as the technical leader championing quality across the team.

Responsibilities

Drive the automation strategy and framework roadmap, and be responsible for the framework architecture and technical standards (design patterns, structure, reusable infrastructure)
Define the automation approach across testing layers: API, service-level, UI, and end-to-end, including mocking and sandbox strategies for third-party payment providers
Own automation quality itself: test stability, flakiness reduction, execution time, and suite reliability
Define and report quality metrics: coverage, pass rate, flakiness, and execution trends
Integrate and evolve automation in CI/CD pipelines (GitHub Actions) for fast, reliable feedback on every change
Represent testability in design and architecture reviews and surface risks early (shift-left)
Partner with developers, product, and manual QA to decide what gets automated, at which layer, and what does not
Evaluate and introduce new tools and approaches, including AI-assisted testing workflows

Were looking for someone who thrives in a fast-moving remote environment, takes ownership end-to-end, communicates clearly, and can independently drive projects from concept to production.



Responsibilities

Design and develop scalable, performant, and maintainable frontend applications using React, TypeScript, and modern web technologies.
Build reusable UI components, shared libraries, and SDKs that support multiple products and integrations.
Collaborate closely with Product, Design, Backend, and Customer-facing teams to deliver intuitive and reliable user experiences.
Own features end-to-end - from technical planning and architecture through implementation, testing, deployment, and monitoring.
Optimize application performance, responsiveness, and reliability across devices and browsers.
Ensure high engineering standards through code reviews, testing, documentation, and observability.
Publish and manage SDK and NPM package versions, including backward compatibility and release management.
Help improve development workflows, tooling, and engineering best practices across the frontend ecosystem.
Contribute to building a strong engineering culture focused on quality, ownership, collaboration, and continuous improvement.

As a QA Engineer, you will play a key role in ensuring the quality, reliability, and flawless execution of core systems. Youll work on high-scale, cloud-native services that power critical payment and business flows, taking ownership of the testing lifecycle - from test planning and execution to production monitoring and continuous improvement. Youll collaborate closely with engineers, product managers, and other stakeholders to maintain our high engineering standards and deliver a seamless experience for our publishers and their users

We are looking for someone analytical, detail oriented, and comfortable working in an agile environment.

If you are passionate about identifying potential issues early, and making a lasting impact on quality processes in a dynamic and rapid-growth environment, this is the place for you!

Responsibilities:

Analyze product requirements, technical designs, and user flows to identify gaps, risks, and missing scenarios early in the development cycle
Create test plans and risk based testing strategies for complex features, around payment flows and integrations
Investigate issues using logs, and monitoring systems
Perform robust API, UI, and integration testing across multiple regions, currencies, and devices.
Lead efforts to identify automation gaps and continuously raise the bar on test effectiveness and coverage.
Leverage AI tools to accelerate workflows and improve quality strategy and execution.

As a Senior FullStack Engineer, youll join our engineering team and help build the next generation of Irregulars products as they evolve into intuitive, polished, and powerful experiences for some of the most sophisticated AI organizations in the world.

This is a highly impactful role for an engineer with strong frontend expertise who cares deeply about product quality and user experience, and can both build scalable systems and help lead the technical direction of the frontend. Youll work closely with exceptional engineers, researchers, and founders to turn deeply technical capabilities into user-facing products that are clear, elegant, and highly effective.

Representative Responsibilities:

Build and own full-stack product features end-to-end

Help shape the next generation of the companys products

Lead the technical direction of the frontend architecture, development standards, and engineering culture

Build polished, high-quality user experiences for highly technical users

Collaborate closely with engineers, founders, and product stakeholders on product and technical decisions

Take ownership of projects from idea to production with high autonomy and impact

Youll be building infrastructure that supports work with frontier AI labs such as Google, Anthropic, and OpenAI, and meets the scale, security, and reliability standards this ecosystem requires. This includes architecting ephemeral, on-demand environments, and spinning up and tearing down multi-service deployments (VPCs, compute, serverless components, and more) as needed.

You will work closely with research, engineering, security, and leadership to design and maintain scalable infrastructure, improve system reliability, and enable fast, safe, and secure product delivery.

Key Responsibilities

Own and evolve Irregulars cloud infrastructure, with a strong focus on scalability, security, and reliability

Design, build, and maintain end-to-end CI/CD pipelines and deployment workflows

Lead and continuously improve containerized environments (Docker, Kubernetes)

Build and maintain Infrastructure as Code and automation frameworks (e.g., Terraform)

Own production readiness: availability, monitoring, logging, alerting, and incident response

Work closely with engineering and research teams to support development, testing, and production needs

Drive improvements in system performance, reliability, and security posture

Take part in - and often lead architectural decisions and long-term infrastructure planning

Act as a key operational owner in a fast-growing startup, setting best practices and standards

As a Technical Policy researcher, you'll tackle some of the biggest and most complex questions of AI development and deployment. Your work outlining problems, solutions and principles for governments, frontier labs, and deployers will shape the emerging field of AI security.

Representative projects:

Threat modeling and fleshing out in what specific way could a strong cyber-capable model cause harm.

Taxonomies for dangerous AI capabilities or mitigations.

Policy proposals for models' refusal policy (which prompts models should refuse to follow).

Following up on publications and news on AI policy, AI risks and mitigations, and technical AI research.

Writing academic papers and blog posts detailing our research around evaluation theory or mitigation recommendations.

Publishing your research and/or delivering research to our customers.

We are looking for a D2C Operations Specialist to take ownership of the setup, configuration, and day-to-day operations of DTC stores.

In this role, you will support store launches, manage operational workflows, maintain store data and configurations, and ensure stores are ready to scale. You will work closely with Engineering, Data, Performance, CRO, Creative, and Partnerships teams to keep operations running smoothly.

What you'll do
Set up, configure, and maintain eCommerce stores, backend systems, and operational tools.
Upload products, manage catalogs, configure pricing, and support store launches.
Build and optimize automations for
operational workflows, leveraging tools, data, and AI-driven processes to improve efficiency, reduce manual work, and support scale.
Monitor day-to-day operations and troubleshoot technical or operational issues.
Work closely with Engineering, Data, Performance, CRO, Creative, and Partnerships teams to improve workflows and scale operations.

We are looking for a Senior AI Engineer to design and build the intelligence layer .

You will own the agentic workflows, LLM integrations, and reasoning pipelines that allow our AI agents to autonomously analyze markets, make decisions, and drive eCom growth at scale.

What you'll do
Design & Build Agentic Workflows: Architect multi-agent pipelines - including planning, memory, tool use, and decision loops - that power autonomous media buying and growth operations.
Own LLM Integration: Select, prompt-engineer, fine-tune, and evaluate LLMs to produce reliable, high-quality outputs across diverse business tasks.
Build RAG Systems: Develop retrieval-augmented generation pipelines with vector search and context management to ground agent reasoning in real business data.
Drive Evaluation & Reliability: Define evals, build testing frameworks, and continuously improve agent output quality, consistency, and safety in production.
Collaborate Across the Stack: Work closely with backend engineers to integrate AI capabilities into core product APIs, ensuring low-latency, production-grade deployment.

We are looking for a Senior Data Engineer with a strong Backend Engineering background to architect the intelligent data foundation.

This is not a traditional ETL role. You will build the critical infrastructure that feeds our Agentic Growth Engine, enabling AI agents to perceive the market, make decisions, and drive growth. You will own the semantic layer, design the agentic data architecture (both data retrieval and training infrastructure), and build sophisticated extraction processes that allow our system to "read" the competitive landscape.

What you'll do
Architect the Agentic Data Infrastructure: Design and maintain the core data pipelines and storage systems (GCP/BigQuery/Postgres) that power our AI agents, ensuring high availability and low latency for decision-making.
Build the RAG & ML Backbone: manage the infrastructure for training data, vector search, and regression testing. You will ensure our agents have access to clean, context-aware data for RAG workflows.
Develop Agentic Extraction Processes: Build complex, resilient data extraction systems (crawlers/scrapers) to map competitive landscapes and product trends, feeding raw market data into our analysis engine.
Own the ELT & Semantic Layer: Manage the transformation of raw data into a consistent, business-ready semantic layer that serves as the "source of truth" for both analytics and AI models.
Run Predictive Models: Operationalize and deploy predictive models on top of our data, integrating them into the core product workflow.Define Data Standards: As a senior owner, you will establish the data engineering best practices, coding standards, and architectural patterns that the rest of the engineering team will follow.

We are a fast-growing cybersecurity startup redefining how organizations protect themselves. Our Data Team is at the heart of that mission - powering everything from security insights to customer-facing intelligence. We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

We are seeking a highly motivated, technically adept, and process-oriented Customer Operations to join our growing team. In this role, you will lead strategic initiatives that automate and optimize workflows across customer and partner operations - playing a pivotal role in streamlining internal systems, building platform integrations, and ensuring scalable, secure, and reliable technical operations.
This is a highly cross-functional position that requires close collaboration with Product, Engineering, and Customer Engineering teams. You will translate operational challenges into technical solutions and drive end-to-end implementation, with a direct impact on how our team scales.
The ideal candidate brings a strong background in systems integration, API-based automation, and SaaS operations. You are passionate about reducing manual overhead, improving the customer experience, and applying technology to solve real-world business problems. You will have a unique opportunity to shape our operational tech stack and define our automation strategy at scale.
Responsibilities:
Lead the design and execution of automation initiatives that enhance internal workflows across customer success, partner onboarding, support, and technical operations.
Identify, prioritize, and scope automation opportunities that reduce manual effort, improve system reliability, and enable self-service capabilities.
Implement integrations and workflow automations between internal platforms (e.g., Salesforce, SharePoint, Slack, Jira, internal admin tools) using APIs, cloud services, and scripting tools.
Partner with Customer Engineering, Engineering, and Product teams to gather requirements, translate them into technical specifications, and manage end-to-end delivery of automation projects.
Own project planning and execution across multiple workstreams, maintaining clear documentation, proactive communication, and strong stakeholder alignment.
Drive standardization of operational processes and help scale technical infrastructure to support customer and partner growth.
Monitor, measure, and report on automation effectiveness and business impact, using data to guide continuous improvement.
Coordinate feature rollouts - from early adopter programs through full production releases - including field coordination and customer communications.
Manage and facilitate customer migrations as required.
Stay current with SaaS, DevOps, and automation industry trends, and proactively apply best practices across the team.
Perform hands-on troubleshooting and root-cause analysis of customer and operational issues, driving timely resolution.
Build, deploy, and maintain internal tools and services, including containerized deployments (Docker / Docker Compose) and supporting automation scripts.

Required System QA Engineer
The Mission
Your role is to ensure the operational stability and resilience of the Applications Ecosystem, encompassing National C2, MSC2, and Edge C2 platforms. You will rigorously test the seams where these distributed systems integrate. You are expected to execute with precision, learn the architecture deeply from the ground up, and evolve into the Domain Expert
for our multi-tiered command and control system. Critically, you will champion a "Shift-Left" quality approach: preventing defects during the design and planning phases rather than merely catching them after development is complete.
Core Responsibilities:
Actively participate in Product Requirements(PRD), High-Level (HLD) reviews to enforce system testability before code is written.
Execute and automate comprehensive test plans across Edge C2 nodes, MSC2 instances, and National C2 cloud environments.
Validate complex data flows and state synchronization across geographically distributed components.
Simulate degraded network conditions, forced disconnects, and VPN tunnel collapses to validate system recovery and data integrity.
Isolate integration breakdowns between Web Applications and backend microservices.
Analyze complex system logs using modern observability tools to provide developers with exact root-cause indicators and precise reproduction steps.
Integrate automated test suites into the CI/CD pipeline to ensure continuous validation.
Maintain clear, artifact-based documentation of test coverage, system behavior, and defect tracking.

Required RF/HW & System Validation Engineer
Scope:
As an RF/HW Validation Engineer, you will bridge the gap between HW/RF validation and complex system-level testing. You will design, develop, and execute automated and manual test plans to verify the performance, reliability, and compliance of our SDR (Software Defined Radio) architectures and multi-layered tactical systems (including integration with other systems).
Key Responsibilities:
System-Level Testing: Execute end-to-end system testing of counter-drone platforms, verifying the integration of RF hardware, firmware, and complex software-defined radio algorithms under real-world scenarios.
Hardware Product Testing: Test and validate various HW products, including antennas, radar systems, jammers, and related peripherals.
Failure Analysis & Troubleshooting: Debug complex RF anomalies, signal integrity issues, and system bugs down to the component/board level, working closely with RF Design, Board Design, and SW teams.
Documentation: Create comprehensive test plans (ATP/DTP), write test reports, and present data-driven analysis to cross-functional R&D teams to impact the next generation of hardware.

We are looking for an experienced system engineer to participate and lead the development of a radio-based drone detection and mitigation system as part of the company products.
Responsibilities:
Lead features and platforms from ideas to releases.
Guide and participate in the research and analysis of both proprietary and standard radio communication
protocols.
Develop and optimize algorithms for scanning, signal separation, antenna selection, etc.
Define requirements and guide other multi-disciplinary teams (SW, Modem algorithms, DSP, and FPGA) through
implementation and debugging.
Analyze and define complex system behaviors, state machines, algorithms, and event-response logic, including
radio link budget considerations.
Perform independent, hands-on debugging and optimization for system problem-solving using tools like
MATLAB, Python, Excel, and other log analysis software.
Gain a deep understanding of the full system to guide and support development, testing and validation teams.