Juniper Square - Senior Software Engineer, Data (AI)
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Requirements
• 4–7 years of software engineering experience, with a track record of shipping production systems end-to-end • Strong backend engineering fundamentals - backend services, data pipelines, and API design; we will ask you to walk through systems you personally built • Hands-on experience with data pipeline or data warehouse engineering: ETL/ELT patterns, schema design, normalization, and data distribution • Production experience building with LLMs - prompt design, model integration, and output validation in real systems • Fluency with AI-assisted and agentic development workflows; you use these tools daily and evaluate their output critically • Experience with AWS data infrastructure; Redshift experience a plus • Strong written communication - able to document technical decisions clearly for engineering and product audiences • Ability to critically evaluate AI-generated code and outputs, including identifying failure modes and regressions • Preferred • Experience with RAG pipelines, vector stores (e.g., OpenSearch, pgvector), or document extraction systems • Background in financial services data - familiarity with fund administration, investment data schemas, or institutional reporting workflows is a meaningful differentiator • Experience building data products for external customers, not just internal tooling • Familiarity with evaluation frameworks for AI outputs: deterministic checks, cross-model comparison, or human-in-the-loop review patterns
Responsibilities
• Deliver Core Data Pipeline Components • Build and ship production-quality implementations of data normalization, schema mapping, validation, enrichment, and distribution pipelines for a net-new intelligent data warehouse • Write clean, well-tested, performant code across backend services, data pipeline logic, and API integrations • Take end-to-end ownership of features from design through deployment, with accountability for correctness and reliability in production • Contribute to Technical Architecture • Work closely with Staff engineers to shape the architecture of a modern, AI-native data warehouse serving institutional financial clients • Bring thoughtful input on schema design, normalization approaches, and API patterns - and execute those decisions with precision • Identify and raise technical risks early; propose and implement solutions rather than waiting to be directed • Build and Operate with AI-Native Practices • Use agentic coding tools and LLM-assisted development as your primary workflow - this is how the entire team operates • Critically evaluate AI-generated code for correctness, edge cases, and regressions - shipping quality output regardless of how it was produced • Contribute to the team's evolving practices around AI-accelerated development and testing • Support Data Quality and Reliability • Build and maintain data validation checks, monitoring, and observability tooling that keeps pipelines trustworthy at scale • Participate in on-call and production support, diagnosing and resolving data quality issues quickly and thoroughly • Write and maintain clear technical documentation for the systems you build
Benefits
• Compensation for this position includes a base salary, equity, and a variety of benefits. The U.S. base salary range for this role is $185,000 – $225,000 USD. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. • Health, dental, and vision care for you and your family • Life insurance • Mental wellness coverage • Fertility and growing family support • Flex Time Off in addition to company-paid holidays • Paid family leave, medical leave, and bereavement leave policies • Retirement saving plans • Allowance to customize your work and technology setup at home • Annual professional development stipend • Your recruiter can provide additional details about compensation and benefits.
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