Software Engineer, Data – AI

Job Description:

• 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
• 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

• 7+ 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.

• 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