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We are looking for a Technical Support member with experience and technical background to handle case reproduction in the support LAB.
Key Responsibilities:
As a support LAB assistant, you will be required to simulate issues in the LAB and maintain the LAB environment for our global and domestic employees.
You will work together with our global and local interfaces to simulate problems on the LAB and provide feedback to the agent that handling the case.
Use Salesforce to manage cases.
Ability to work on flexible hours.

We are looking for an experienced, opinionated, and highly technical Staff Data Engineer to define the long-term direction of our Data Platform.
This role is ideal for a senior data leader who combines deep hands-on expertise with strong architectural judgment, enjoys mentoring others, and takes full ownership of complex, high-scale data systems.
You will drive platform architecture, set engineering standards, and lead the design and delivery of scalable batch and streaming data solutions on AWS.
Key Responsibilities:
Technical Leadership & Architecture:
Own and evolve the overall data platform architecture-scalability, reliability, security, and maintainability.
Lead the long-term strategic direction of the platform, balancing performance, cost, and operational excellence.
Introduce and drive adoption of modern data paradigms: lakehouse (Iceberg), event-driven pipelines, schema-aware processing.
Data Lake & Architecture Ownership:
Design, model, and evolve the Data Lake architecture, including:
Storage layout and data organization
Data formats and table design (e.g., Iceberg)
Batch and streaming ingestion patterns
Schema governance and lifecycle policies
Define and promote best practices for data modeling, partitioning, and data quality.
Ensure the Data Lake supports analytics, ML workloads, and operational systems at scale.
Platform Engineering:
Design and build high-scale ETL/ELT pipelines leveraging Apache Spark (EMR/Glue) and AWS-native services.
Optimize production-grade pipelines using S3, Athena, Kinesis, Lambda, Step Functions, and EKS.
Lead the rollout of modern patterns such as lakehouse architectures and event-driven data pipelines.
Security & Governance:
Ensure alignment with AWS security best practices-IAM, encryption, auditing, and compliance frameworks.
Partner with security and governance teams to support regulated and sensitive data environments.
Mentorship & Collaboration:
Serve as a technical mentor to data engineers; elevate team capabilities.
Lead architecture reviews and cross-team design discussions.
Work closely with Data Science, ML Engineering, Backend, and Product teams to deliver end‑to‑end data solutions.

We are looking for an experienced and visionary Staff Data Architect to play a critical role in defining and shaping the data architecture for our flagship investigative analytics platform. In this position, you will design and guide the implementation of robust, scalable, and secure data pipelines that power advanced data processing for AI-driven insights as part of digital investigations.
You will work closely with cross-functional teams to drive technology alignment and ensure architectural excellence across multiple domains. This is a high-impact role, ideal for someone with deep technical expertise and strong strategic thinking, who thrives in a dynamic, collaborative environment and is passionate about building world-class technology platforms.
As our Data Architect, you will own the vision for how we manage, move, and leverage data within our SaaS product suite. Your role is pivotal in designing and implementing a robust data architecture that supports both real-time operational needs and advanced analytics, all within a scalable and cost-effective cloud-native environment.
Responsibilities:
Own the Data Vision: Take ownership of the data architecture, including our data lake, data warehouse, and ETL/ELT pipelines, to support our product teams and business intelligence.
Cost Optimization & Scalability: Provide architectural leadership and guidance to ensure our data platforms are designed for cost efficiency and scalability, actively identifying and implementing opportunities to optimize cloud spend.
Product-Centric Collaboration: Collaborate with engineering, product, data science, and security teams to translate product requirements and business needs into a strategic data architecture that drives product innovation.
Design & Governance: Conduct deep architecture reviews, assess technical risks, and provide recommendations to ensure data quality, security, and governance are embedded into every product.
Standardization & Enablement: Define and standardize data modeling practices, governance frameworks, and data pipeline patterns to enable efficient and consistent data development across product teams.
Technology Evolution: Evaluate new data technologies, tools, and methodologies (e.g., streaming platforms, modern data warehouses) to continuously improve our data platforms.
Documentation & Mentorship: Document architectural decisions, data flow diagrams, and cost models. Act as a mentor and technical authority, fostering a culture of technical excellence and cost-awareness.

We are assembling a highly skilled, small-scale engineering team focused on transforming generative AI innovation into real, production-grade platforms.
As a Platform Engineer with a strong backend orientation, you will architect and implement the core infrastructure that enables rapid deployment, experimentation, and scaling of advanced AI capabilities. Your work will bridge cutting-edge research with reliable, secure, high-performance systems powering the next generation of digital intelligence products.
Responsibilities:
Design and develop backend services and APIs for SaaS applications using Node.js and TypeScript
Architect and implement microservices and distributed systems optimized for scalability and maintainability
Build and maintain CI/CD pipelines for automated deployments and testing
Develop cloud-native solutions leveraging AWS services and Kubernetes (EKS)
Manage infrastructure as code using Terraform and Helm for Kubernetes deployments
Ensure system reliability, security, observability, and performance at scale
Collaborate with cross-functional teams to deliver features in an agile environment
Continuously improve platform architecture and development workflows.

Required Senior Cloud Security Architect
Position Overview:
As a Cloud Security Architect, you will be responsible for defining and strengthening the security posture of our products and cloud environments. You will lead threat modeling, risk assessments, and the design of secure architectures, while guiding teams in implementing effective security controls and secure development practices. Working closely with developers, engineers, and management, you will ensure security is embedded throughout the product lifecycle and clearly communicate complex concepts across the organization. This role requires strong technical expertise, strategic thinking, and a proactive approach to emerging threats.
Key Responsibilities:
Conduct Threat Modeling and Security Risk Assessment to identify weaknesses in existing security measures and develop strategies to address them.
Design Security Architecture that withstand attacks and ensure the confidentiality, integrity, and availability of the product. This involves establishing secure configurations, access controls, authentication mechanisms, and encryption methodologies.
Implementing Security Controls guiding the integration of secure coding practices, establishing secure development lifecycles, and ensuring adherence to established security standards.
Collaborate with stakeholders including developers, engineers, and management teams. Communicate complex security concepts in a clear and concise manner, ensuring that all parties understand the importance of incorporating security measures into the product development process.
Stay updated with emerging threats and remain vigilant, continuously monitoring emerging threats and vulnerabilities.

We are seeking a Senior Backend & Data Engineer to join its SaaS Data Platform team.
This role offers a unique opportunity to design and build large-scale, high-performance data platforms and backend services that power our cloud-based products.
You will own features end to end-from architecture and design through development and production deployment-while working closely with Data Science, Machine Learning, DevOps, and Product teams.
What Youll Do:
Design, develop, and maintain scalable, secure data platforms and backend services on AWS.
Build batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS.
Develop backend components and data-processing workflows in a cloud-native environment.
Optimize performance, reliability, and observability of data pipelines and backend services.
Collaborate with ML, backend, DevOps, and product teams to deliver data-powered solutions.
Drive best practices, code quality, and technical excellence within the team.
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing).
Tech Stack:
AWS Services: S3, Lambda, Glue, Step Functions, Kinesis, Athena, EMR, Airflow, Iceberg, EKS, SNS/SQS, EventBridge
Languages: Python (Node.js/TypeScript a plus)
Data & Processing: batch & streaming pipelines, distributed computing, serverless architectures, big data workflows
Tooling: CI/CD, GitHub, IaC (Terraform/CDK/SAM), containerized environments, Kubernetes
Observability: CloudWatch, Splunk, Grafana, Datadog
Key Responsibilities:
Design, develop, and maintain scalable, secure backend services and data platforms on AWS
Build and operate batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS
Develop backend components and data processing workflows in a cloud-native environment
Optimize performance, reliability, and observability of data pipelines and backend services
Collaborate with ML, backend, DevOps, and product teams to deliver data-driven solutions
Lead best practices in code quality, architecture, and technical excellence
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing)