Principal Data / AI Architect

Brightside

13d

About The Position

Brightside is seeking a Principal Architect, Data & AI Platforms, to own and evolve the technical foundations that power our AI-driven experiences, platform integrations, and analytics. This is a senior, hands-on architecture role designed for someone who combines deep data architecture expertise, strong applied AI judgment, and the ability to translate business strategy into durable technical systems. This role reports directly to the CTO and serves as the CTO’s right-hand partner for data, AI, and platform architecture decisions. You will have clear decision authority over data and AI architecture across engineering teams, while partnering closely with Product, Analytics, and Engineering leadership to ensure speed, quality, and long-term integrity. This is not a research role, nor a people-management role. It is an execution-oriented architecture leadership role focused on clarity, leverage, and outcomes.

Requirements

10+ years of experience in software engineering, data architecture, or systems architecture, with significant hands-on experience
Deep expertise in data architecture and data modeling, including relational databases, event-driven systems, and analytical data platforms
Strong experience designing and operating data platforms at scale, including data lakes/warehouses and real-time pipelines
Strong experience designing and operating AI/ML systems in production, including LLM-based architectures (RAG, embeddings, vector databases, prompt orchestration)
Proven experience in regulated environments (fintech, financial services, healthcare, etc.), with an understanding of data privacy, security, and compliance requirements
Strong in modern cloud architectures (e.g., AWS) and modern data stacks (e.g., Databricks)
Ability to connect technical decisions to business outcomes, including cost efficiency, scalability, risk mitigation, and customer experience
Strong communication skills and comfort influencing across engineering, product, and executive leadership
Experience serving as a Lead Architect in a high-growth or transformation-stage company

Nice To Haves

Background in financial systems, payments, lending, or financial data platforms
Experience with AI governance, model risk management, or explainability frameworks
Track record of improving engineer productivity through platform and architecture design

Responsibilities

Own the data and AI architecture across the company, spanning: AI-powered systems and decisioning workflows Core application platforms Analytics and reporting layers
Define and evolve canonical data models across clients, employers, partners, financial products, and outcomes
Ensure consistency across transactional systems, analytical platforms, and AI feature layers
Act as the company’s data strategy expert, with deep understanding of: Employer integrations (eligibility, payroll, SSO, identity) Partner integrations and product data External and enrichment data sources (e.g., credit, public datasets)
Identify which data sources meaningfully compound business and product value, and which do not
Guide integration and platform investments based on data leverage and long-term value, not just feature demand
Design and govern production-grade AI systems, including: LLM-based applications (RAG, prompt orchestration, embeddings, vector stores) Decisioning and automation workflows
Evaluate and govern AI models and platforms (e.g., OpenAI, Anthropic, open-source), balancing: Accuracy and reliability Cost and latency Security, privacy, and explainability
Define standards for AI lifecycle management (build, deploy, monitor, iterate, retire)
Act as the decision-maker for data and AI architecture decisions across engineering teams
Partner with the Enterprise Architecture Board to review proposals, surface risks, and ensure coherence
Establish clear architecture standards and review processes that enable teams to move fast without creating long-term risk or technical debt
Lead rapid prototyping and technical discovery to: Test architectural assumptions Evaluate new AI approaches Inform investment and roadmap decisions
Personally build or lead proofs-of-concept where needed to drive alignment and reduce uncertainty
Partner closely with the CTO, Product leaders, Analytics, and Engineering to: Translate business strategy into technical direction Align data, AI, and platform investments Serve as a trusted technical advisor to executive leadership on data, AI, and platform tradeoffs