Design and implement autonomous AI agents to manage the sales lifecycle, including lead qualification and CRM synchronization. Collaborate with cross-functional teams to optimize AI performance through prompt engineering and continuous experimentation.
Blend360
38 Remote Job Openings at Blend360
You will design and implement scalable, domain-oriented data solutions and reliable pipelines on AWS. You will also collaborate with cross-functional teams to align technical solutions with business requirements and optimize data workflows.
The analyst will support the implementation and analysis of quantitative research projects, including programming surveys and managing research instruments. They will also assist in creating reports, maintaining research repositories, and tracking project progress across the enterprise.
The Senior Data Engineer will build, maintain, and optimize scalable data pipelines and modular components within Databricks to support journey analytics. This role involves refactoring legacy codebases and ensuring high-quality, performant datasets for reporting and cross-functional use cases.
Lead and mentor a team of data engineers while defining the technical strategy for Journey Analytics data platforms. Actively contribute to the design, implementation, and maintenance of scalable, high-quality data pipelines and models.
Support the implementation and analysis of quantitative research projects, including the development and deployment of surveys via Qualtrics. Assist in creating reports, managing the market intelligence repository, and supporting VoC and VoE programs.
The role involves designing and implementing standardized ETL pipelines and data models to migrate data from over 80 ERP systems into Microsoft Fabric. The Lead will establish data quality frameworks and mentor team members to ensure a unified, AI-ready data architecture.
Lead the design and implementation of standardized ETL pipelines and data transformation processes to migrate ERP data into Microsoft Fabric. Establish data quality frameworks and mentor team members on engineering practices to create an AI-ready data architecture.
Design and deploy AI-powered applications using LLMs and RAG to automate corporate finance processes and generate business insights. Build integrations between AI solutions and enterprise planning platforms while ensuring compliance with corporate governance and security standards.
Design, develop, and deploy scalable AI solutions utilizing RAG, agentic frameworks, and MLOps workflows. Collaborate across engineering teams to align innovative AI systems with broader development goals and performance monitoring.
Lead the end-to-end delivery of production-ready AI systems, including RAG pipelines and agentic frameworks. Design evaluation strategies and automate the MLOps/LLMOps lifecycle to ensure scalable and reliable AI solutions.
Design intuitive, enterprise-grade user interfaces and scalable design systems using Figma. Lead the end-to-end UX design for complex data review and approval workflows while collaborating with cross-functional stakeholders.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to power analytics and business-critical workflows. Collaborate with cross-functional teams to optimize batch and streaming ingestion architectures while ensuring data quality and governance.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to power analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to power analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
Design, develop, and maintain full-stack web applications using React and Python while integrating AWS cloud services. Collaborate with cross-functional teams to implement scalable features and optimize application performance.
Design, develop, and maintain frontend and backend components of modern web applications using React and Python. Collaborate with cross-functional teams to architect scalable cloud solutions on AWS and optimize application performance.
Design, develop, and maintain frontend and backend components of modern web applications using React and Python. Collaborate with cross-functional teams to architect scalable cloud solutions on AWS and optimize application performance.
Design, develop, and maintain frontend and backend components of modern web applications using React and Python. Collaborate with cross-functional teams to architect scalable cloud solutions on AWS and optimize overall application performance.
Design, develop, and deploy machine learning models to solve business problems while writing production-level code. Collaborate with cross-functional teams to integrate models into production and provide technical mentorship to junior team members.
Design, develop, and deploy machine learning models to solve complex business problems while writing production-level code. Collaborate with cross-functional teams to integrate models into production and implement MLOps best practices.
Design and implement a data quality framework across Bronze, Silver, and Gold layers while maintaining automated checks within Databricks pipelines. Collaborate with Data Engineering and business teams to validate data pipelines, perform reconciliation, and ensure production-ready data assets.
Design and implement a comprehensive data quality framework across Bronze, Silver, and Gold layers within Databricks pipelines. Collaborate with data engineering and business teams to validate data accuracy, perform reconciliation, and monitor pipeline health post-deployment.
The Data Quality Engineer will design and implement a data quality framework across Bronze, Silver, and Gold layers while maintaining automated checks within Databricks pipelines. They will also collaborate with Data Engineering teams to validate data flows and ensure production-ready data assets.
Design and implement a comprehensive data quality framework across Bronze, Silver, and Gold layers within Databricks pipelines. Collaborate with Data Engineering and business teams to validate data pipelines, perform reconciliation, and ensure production-ready data assets.
The Data Science Manager will lead advanced analytics initiatives, including the design and implementation of predictive models to optimize customer journeys. They will also collaborate with cross-functional stakeholders to define data-driven strategies and mentor a team of data scientists.
The QA Analyst will design and implement data quality frameworks and automated checks across Databricks pipelines to ensure data reliability. They will also collaborate with data engineers and business stakeholders to validate end-to-end data flows and support user acceptance testing.
Design and implement a data quality framework across Bronze, Silver, and Gold layers while building automated checks within Databricks pipelines. Collaborate with Data Engineering and business teams to validate data flows and ensure production-ready data assets.
The QA Analyst will design and implement data quality frameworks and automated checks across Databricks pipelines to ensure data reliability. They will also collaborate with data engineers and business stakeholders to validate data assets and resolve quality incidents.
Design and implement a data quality framework across Bronze, Silver, and Gold layers while building automated checks within Databricks pipelines. Collaborate with data engineers and business stakeholders to validate data flows and ensure production-ready data assets.
The role involves building, maintaining, and optimizing scalable data pipelines and modular components to support journey analytics. You will refactor legacy code and collaborate with cross-functional teams to ensure high-quality, performant datasets.
The QA Analyst will design and implement data quality frameworks and automated checks across Bronze, Silver, and Gold layers in Databricks. They will also collaborate with Data Engineering and business teams to validate data pipelines and ensure accurate, production-ready data assets.
Take ownership of complex frontend initiatives and drive them from concept to production with minimal supervision. Develop robust, reusable, and scalable components while ensuring compliance with security standards and optimizing performance.