Staff Software Engineer, Data (AI)

Juniper Square is an Operations Partner providing technology, data, and fund administration services for private markets. The Staff Software Engineer, Data will design and deliver core components of a next-generation intelligent data platform, including data normalization, schema mapping, validation, enrichment, and distribution. The role also involves defining architecture, building AI evaluation infrastructure, using AI-native development practices, and establishing technical standards.

Responsibilities:

• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse
• Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others
• Take technical ownership from architecture through deployment, with accountability for reliability, performance, and correctness
• Partner with a small seed team to define the end-to-end architecture for an AI-native data warehouse serving institutional financial clients
• Bring opinionated decisions on schema design, normalization strategies, API exposure patterns, and data distribution approaches
• Evaluate and select technologies with a bias toward what ships well and scales sustainably
• Design and implement the evaluation framework that makes AI-generated outputs trustworthy in high-stakes financial data contexts
• Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows
• Contribute to shared AI evaluation infrastructure that can serve as a foundation across multiple products
• Use agentic coding tools and LLM-assisted development as your primary workflow - this is how the entire team operates
• Bring strong opinions about how to get the most from AI-assisted development while maintaining quality and reliability
• Contribute to the team's evolving practices around AI-accelerated SDLC
• Set coding standards, review practices, and architectural documentation that will scale as the team grows
• Help define what "good" looks like for a team building at speed without sacrificing quality
• Mentor engineers and provide technical guidance as the team expands

Requirements:

• 12+ years of software engineering experience, with demonstrated Staff-level technical scope and impact
• A portfolio of shipped production systems - we will ask you to walk through specific technical decisions you personally made and code you personally wrote; this is not a role for someone whose primary contribution has been directing others
• Strong hands-on experience with data pipeline or data warehouse engineering: schema design, ETL/ELT patterns, normalization, and API-based data distribution
• Production experience building with LLMs: prompt design, model orchestration, evaluation, and output validation in real systems, not just experimentation
• Fluency with AI-assisted and agentic development workflows; you use these tools daily and have strong opinions about how to use them effectively
• Experience with AWS data infrastructure; Redshift experience a plus
• Strong written communication —- able to translate technical design into clear documentation for both engineering and product audiences
• Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases
• Experience with RAG pipelines, vector stores, or document extraction systems
• Background in financial services data — familiarity with fund administration, investment data schemas, institutional reporting workflows, or related domains is a meaningful differentiator
• Experience building data products or managed data services for external customers, not just internal tooling
• Prior experience in a technical lead or TLM capacity on a new or early-stage product team