Jobs at Quantiphi

The Senior Sales Engineer will develop GTM strategies, drive market expansion and revenue growth in the BFSI sector by engaging clients and managing key accounts.

The Senior Business Analyst will analyze and solve complex problems in the Insurance industry, lead project teams, gather requirements, and develop innovative solutions using advanced analytics and machine learning.

Architect and implement MLOps strategies, design ML pipelines, mentor teams, and ensure compliance on Google Cloud, focusing on AI/ML best practices.

The role involves leading EKS audits, architecting consolidation plans, defining networking strategies, establishing security measures, and designing CI/CD infrastructure.

Lead application migration and modernization initiatives to AWS, utilizing cloud-native practices and providing technical leadership for development teams.

Responsible for developing and maintaining chatbot applications, collaborating with business partners on requirements, and enhancing chatbot capabilities using AI/NLP technologies.

The Machine Learning Engineer develops and optimizes workflows, implements advanced AI models and tools, and collaborates on data pipelines. Responsibilities include fine-tuning models and optimizing deployments for performance and cost.

The Associate Engagement Manager manages client relationships, leads project delivery, guides teams on technical issues, and drives business opportunities. They ensure effective communication and problem-solving while aligning with business goals.

Support data flow design, implement Azure solutions, write code for ML workflows, manage development tasks, and coordinate testing activities.

Design and maintain scalable Azure infrastructure, implement CI/CD pipelines, optimize AI model performance, and ensure compliance with AI standards.

The Senior Machine Learning Engineer will develop and optimize workflows, implement advanced RAG capabilities, build data pipelines, and fine-tune models while collaborating closely with Data Engineers.

Design and implement data integration solutions between Azure AI and SAP systems, ensuring data integrity, security, and optimal performance.

The Research Engineer will innovate in AI, focusing on ML concepts, developing large language models, and contributing to AI research through prototyping and publications.

Lead design and implementation of a next-generation data layer for agentic AI: architect hybrid Snowflake/Kinetica/NoSQL environments, define multi-tenant schemas and knowledge graphs, oversee DBA/governance and performance engineering, establish ETL/ELT (CDC/streaming/batch) patterns, and serve as the primary technical client liaison.

The Technical Architect - Machine Learning designs multi-layered AI solutions, defines technical roadmaps, leads model evaluation, and ensures architectural alignment in AI services and governance.

The Associate Architect - Data will design and develop data warehouse solutions using Snowflake on Azure, lead data pipeline development, implement error handling and monitoring, and mentor junior data engineers, focusing on technical solutions for business requirements.

The Senior Data Engineer will design and optimize data pipelines, manage Snowflake features, lead development efforts, and ensure data quality, focusing on financial data processes.

The Engagement Manager will oversee client relationships, project delivery, and team management for data and cloud engagements, ensuring successful project execution and team development.

The role involves leading data migration and modernization strategies, designing scalable AWS solutions, and managing large-scale data projects. Responsibilities include technical leadership, architecture design, project implementation, and mentoring engineers.

The Architect - Machine Learning role involves designing cloud ML solutions on AWS, implementing Generative AI models, and collaborating with cross-functional teams to enhance LLM performance for user-friendly applications.