Teams at Juniper Square

Owns data quality and reliability for data engineering projects by defining testing strategies, building scalable automation frameworks, validating pipelines and analytical platforms, and managing release readiness. The role covers backend and pipeline testing, data integrity, ETL/ELT validation, AI-augmented test development, governance, code reviews, and reducing manual testing. It requires close collaboration with data engineering, product, and data science teams.

Build and operate custom AI agents for private-market clients end to end, from discovery and requirements through deployment, rollout, adoption, and ongoing iteration. Design agentic systems with retrieval, context design, tool and MCP integrations, orchestration, evaluation, observability, and cost controls. Work directly with clients, make product and engineering trade-offs, manage cloud infrastructure, document solutions, train users, and mentor less experienced engineers.

Build and operate custom AI agents for private-market clients across discovery, requirements, design, full-stack development, deployment, and post-launch iteration. Translate ambiguous business needs into reliable software, integrate tools and client systems, establish evaluation and observability practices, and support adoption through documentation, training, and rollout. Collaborate directly with clients and internal platform teams while balancing speed, security, maintainability, and product impact.