Senior Software Engineer, Data – AI

Senior Software Engineer in AI-focused role at Juniper Square. Delivering data pipeline solutions for a next-generation intelligent data platform.

Posted 5/26/2026full-timeRemote • California, New York • 🇺🇸 United StatesSenior💰 $185,000 - $225,000 per yearWebsite

Tools & technologies

Amazon RedshiftAWSETL

Key responsibilities & impact

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
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
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
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

What you’ll need

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.

Comp & perks

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Hard Skills & Tools

data normalizationschema mappingdata validationdata enrichmentdata distributionbackend servicesdata pipeline logicAPI integrationsETLELT

Soft Skills

end-to-end ownershipaccountabilitycritical evaluationproblem-solvingwritten communication