QA Automation Engineer (Python)
Build and maintain scalable automation frameworks and utilities for API and integration testing. Validate AI agents and agentic workflows while evaluating the quality of AI-generated outputs.
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Build and maintain scalable automation frameworks and utilities for API and integration testing. Validate AI agents and agentic workflows while evaluating the quality of AI-generated outputs.
You will design and maintain the public REST API and the orchestration control plane that automates network deployments across global PoPs. This involves managing the full lifecycle of network resources, from developer-facing specs down to router configurations.
You will develop and assist with data and cloud migration frameworks to move on-premise assets to Azure and Snowflake platforms. Additionally, you will maintain software solutions, contribute to agile ceremonies, and collaborate with cross-functional teams to drive client success.
The role involves designing and maintaining automated pipelines for publishing Python packages while improving build infrastructure and CI/CD workflows. You will also focus on strengthening software supply chain security and enhancing the developer experience through intuitive tooling and documentation.
You will collaborate with cross-functional teams and external vendors to deliver high-quality software engineering solutions. The role involves active participation in the development lifecycle, including clarifying requirements and working on diverse projects ranging from startups to global brands.
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The AI Engineer will design, build, and deploy intelligent solutions using modern Machine Learning, Deep Learning, and Generative AI technologies. They will collaborate with engineering, product, and data teams to turn complex business challenges into scalable AI-powered solutions.
You will partner with clients to understand complex business challenges and design, build, and deploy custom AI-powered solutions. This role involves integrating modern AI capabilities into real-world applications while working closely with stakeholders throughout the solution lifecycle.
You will build efficient data-powered REST APIs and end-to-end data pipelines while collaborating with UX designers and front-end engineers. Additionally, you will help define functional requirements with customers and contribute to testing and bug fixes.
You will architect and develop scalable, cloud-native backend services to support ad buying and campaign planning systems. Additionally, you will lead engineering practices, mentor team members, and drive technical strategy across the ad tech ecosystem.
Evaluate the quality and reasoning of AI-generated coding interactions to ensure they align with strong engineering standards. Provide clear, opinionated feedback on the utility and trust-building aspects of AI coding agent outputs.
Evaluate the quality, reasoning, and engineering judgment of AI coding agents in real-world scenarios. Provide clear, opinionated feedback to help define high standards for AI-assisted development interactions.
Evaluate the quality of AI-generated coding interactions by assessing reasoning, utility, and engineering judgment. Provide clear, opinionated feedback to help define high standards for AI-assisted development workflows.
The Senior Python Engineer will lead the audit and optimization of RAG pipelines for industrial automation systems, focusing on reducing AI hallucinations and improving retrieval latency. They will also provide technical supervision to mid-level engineers and ensure high-quality, secure code delivery within an Agile environment.
The role involves designing, developing, and maintaining comprehensive test coverage for a variety of products and features. You will be responsible for implementing automated testing solutions and ensuring high coding standards across the development lifecycle.
Design, build, and operate scalable batch and streaming data pipelines using Python, PySpark, and Azure Databricks. Manage data architecture, orchestration, and CI/CD processes while ensuring high data quality and performance.
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You will design and maintain high-volume data ingestion and ETL pipelines to process telemetry from mobile endpoints. Additionally, you will collaborate with the research team to productionize detection logic and extract complex data from forensic artifacts.
Develop and improve cloud-based software features while investigating new technologies like 5G, OSM, and SDN. Collaborate with squads on bug fixing, participate in Scrum meetings, and contribute to open-source communities.
Design, develop, and maintain enterprise applications, APIs, and identity-driven integrations using Python and Java. Collaborate on architecture reviews and implement secure, scalable solutions across the Okta ecosystem.
Design, develop, and maintain enterprise applications, APIs, and identity-driven integrations within the Okta ecosystem. Collaborate on architecture reviews and implement secure, scalable solutions using Python, Java, and modern integration frameworks.
Design, develop, and maintain enterprise applications, APIs, and identity-driven integrations using Python and Java. Build reusable services and integration accelerators to support identity lifecycle processes and AI agentic applications.
Design, develop, and maintain enterprise applications, APIs, and identity-driven integrations within the Okta ecosystem. Collaborate on architecture reviews and implement secure, scalable solutions using Python and Java.
Design, develop, and maintain scalable, cloud-native applications and microservices using Java and Python. Leverage AI-powered tools to automate engineering workflows and improve developer productivity.
Design, develop, and maintain scalable enterprise backend applications using Java 17+ and Spring Boot. Collaborate within an Agile/Scrum team to deliver high-quality microservices and cloud-native solutions on Azure.
Design, develop, and optimize robust and scalable data pipelines. Implement efficient ETL/ELT processes to handle large volumes of data.
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The role involves designing and developing robust, scalable data pipelines and ETL/ELT processes to handle large volumes of information. You will also be responsible for optimizing batch processes, managing data models, and collaborating with technical teams in an Agile environment.
Develop advanced data science solutions and analytical models while optimizing BigQuery queries and data transformation processes. Collaborate with business and technology teams to define analytical use cases and support machine learning initiatives.
The role involves designing, developing, and maintaining scalable data pipelines and ETL/ELT workflows using Python, SQL, and cloud platforms. You will also collaborate with cross-functional teams to troubleshoot production issues and ensure high-quality data processing solutions.
You will develop and scale open source SDKs, enterprise APIs, and backend systems to support the machine learning lifecycle. You will also write maintainable, performant code to manage large-scale unstructured data for diverse AI applications.
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