Required Senior Software Engineer
Responsibilities:
Own, enhance, and improve our core platform
Build and maintain systems for collecting and processing metrics from client environments
Focus on system efficiency and resilient infrastructure
Integrate well-known SaaS platforms into our big data repository (e.g., major cloud providers, Datadog, Snowflake)
Optimize Spark and Airflow processes
Contribute to data design and platform architecture while working closely with other business units and engineering teams
Face the challenges of testing and monitoring large-scale data pipelines.

Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.

So, what will you be doing all day?

Your role as Data Engineer of the Ingest Data Collection team means your daily responsibilities may include:

Design, code and manage end-to-end data ingestion pipelines, both online and offline.
Take charge of developing & maintaining modern data infrastructure, while implementing best practices for building data pipelines.
Be responsible for high-scale ingestion services, solving challenges of availability, reliability, and scalability.
Run the production environment by monitoring availability and taking a holistic view of system health and data quality.
Own data infrastructure features from design to production using industry best practices with focus on quality and delivery.
Lead design & decision-making processes of the team.
Solve diverse complex problems of scale, performance and business logic.
Collaborate with product managers and other team leaders to plan, nurture, and implement an efficient and effective development process.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products
Perform code reviews, evaluate implementations, and provide feedback about potential improvements.
Improve your skills, learn from and mentor top-notch engineers and enrich other team members.
Have lots of fun!

we are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of decisioning platform.



What you'll be doing:

Design, build, and scale backend systems that power real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are now hiring a talented, self-driven and passionate Senior Data Engineer to build and maintain optimized and highly available data pipelines that facilitate deeper analysis and reporting.
What Youll Do:
Design, develop, and maintain scalable data pipelines that integrate data from multiple sources, including APIs, databases, streaming platforms, edge computing devices, cloud services, and on-premise systems.
Design reliable and business-critical data processing workflows for batch and real-time use cases.
Develop data access services and APIs that enable efficient communication between edge devices, cloud infrastructure, and on-premise environments.
Design and optimize storage solutions for structured, semi-structured, and high-dimensional sensor data to support AI model training, inference, and analytics.
Strong understanding of distributed systems and scalable data processing architectures.
Build and maintain scalable streaming data pipelines for low-latency processing and event-driven architectures.
Analyze existing data architecture, storage models, and processing workflows, and continuously improve performance, scalability, reliability, and maintainability.
Optimize cloud infrastructure and data storage costs while maintaining high availability and low-latency access.
Collaborate closely with Software, AI, Algorithms, DevOps, and Product teams to translate business requirements into scalable technical solutions.
Design monitoring, observability, and operational processes for data platforms.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

As a Staff Software Engineer at our company, you will play a critical role in building our platform. Your expertise and contributions will have a direct impact on the success and effectiveness of our product. Specifically, your responsibilities will include:

Lead, design, architect and build high-quality scalable software by introducing best practices around software engineering architecture and processes
Raise the bar on engineering excellence by improving standard methodologies, producing best-in-class code, documentation, testing, and monitoring
Collaborate with product and R&D engineers to translate product requirements into technical solutions.
Identifying and resolving technical issues and performance bottlenecks.
Staying up to date with the latest industry trends and technologies to continuously improve our products.
Be a mentor for colleagues and help promote knowledge-sharing

We are looking for an experienced QA engineer to lead and drive the Quality of our cloud sensor - the industrys most efficient security tool for monitoring application-layer attacks in real time.

we are a fast-growing cybersecurity startup transforming how organizations protect their applications, cloud environments, and AI systems at runtime. Backed by top-tier investors including Greenfield Partners, Red Dot Capital Partners, Lightspeed, Ballistic Ventures, and TLV Partners, were on a mission to make real-time security a reality.

As our Sensor Quality Lead, youll own the quality of the Sensor - how we test it, and how we prove it works accurately and efficiently across the environments our customers run it in. There's no existing playbook for this role; you'll be the one writing it, tackling complex testing challenges in the Linux systems realm and building the automation that lets us ship with confidence.

In particular:

Design and build automated test frameworks and specialized harnesses for the Sensor
Build and maintain test environments across Kubernetes, Docker, and VMs, including test applications written in different languages, so a single build is validated everywhere it runs
Build the test infrastructure that measures accuracy, performance, and resource consumption under high scale
Define quality metrics for the Sensor, build the test infrastructure that measures them along with dashboards and visibility measures to surface them
Collaborate with the Sensor teams, Product Managers, research, and other R&D teams to deliver end-to-end quality

We are seeking a detail-oriented and collaborative Senior ML Engineer to help support and maintain our machine learning capabilities. This role is ideal for someone who enjoys working closely with production systems, ensuring reliability, scalability, and explainability of models while enabling research teams to deliver impact faster.



Responsibilities



Collaborate with cross-functional teams to ensure ML systems remain robust, explainable, and aligned with business needs.
Monitor and report on ML model performance, reliability, and explainability metrics.
Participate in model retraining procedures, implement automation and optimization of MLOps pipelines.
Extend and scale monitoring pipelines, including support for new features in development.
Investigate, troubleshoot, and resolve issues in production ML workflows (tiered support from initial triage to root-cause analysis with model owners).
Develop and maintain repositories for feature engineering, inference monitoring pipelines, and artifact monitoring tools.
Perform exploratory data analysis (EDA) on historical datasets to identify quality issues and maintain data health.
Implement and oversee production based adjusters across customer deployments.
Evaluate and track critical ML artifacts such as explainability files, coverage metrics, and alignment of features.
Support development and maintenance of internal tools (e.g., interfaces, registries, and feature monitoring frameworks).
Build and maintain static and temporal features, including seasonality, event-based, and price-related features.

You will be working on core B2B platform that serves tens of thousands of customers, serving hundreds of terabytes in production. Our backend engineers are responsible for the entire data lifecycle - from our endless datatlakes, through choosing the right serving methods and databases, all the way to our api services.

So, what will you be doing all day?

Design and implement scalable backend services and libraries that are reusable and maintainable, serving as the foundation for various applications across the company.
Build and maintain tools that streamline development workflows, enabling product teams to focus on delivering business value.
Define and promote best practices for code quality, performance, and reliability, ensuring healthy production environments and rapid development cycles.
Lead the adoption and integration of AI tools to assist in code generation, testing, documentation, and debugging, thereby accelerating development processes.
Perform proof-of-concepts (POCs) on emerging technologies, including AI agents and platforms, to assess their applicability and benefits to our development ecosystem.
Drive cross-team technical projects aimed at improving infrastructure scalability, reliability, and developer experience.
Analyze and resolve complex production issues, ensuring minimal downtime and optimal performance.
Contribute to the evolution of our system architecture, ensuring it supports rapid development and scaling needs.

we are seeking a highly skilled Backend Engineer to join our dynamic team. The ideal candidate will have expertise in Backend technologies, with a strong focus on cloud infrastructures and event-driven architecture. This role will be central to developing and maintaining robust, scalable, and high-performance solutions that secure machine and non-human identities in cutting-edge ecosystems.

What Youll Do
Design, develop, and maintain efficient and scalable cloud-native backend systems with a focus on securing token-based and machine identities.
Build and enhance API integrations with third-party applications to facilitate secure data collection and sharing.
Own the architecture of NHI agent services, ensuring scalability, networking efficiency, robust security, and data storage optimization.
Develop advanced monitoring and automation tools to maintain system stability and deliver performance benchmarks.
Design and implement big data solutions and pipelines for large-scale data processing and analytics using tools like Spark and Snowflake.
Take ownership of projects, driving them end-to-end from ideation and design to development, deployment, and maintenance.
Work collaboratively with cross-functional teams to define, design, and launch innovative features tailored to the NHI ecosystem.
Drive a customer-first mindset by understanding the users' needs and developing solutions that exceed expectations.