Principal Data – AI Architect

Job not on LinkedIn

🕒 March 18

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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BrightSide

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2010

🎯 Recruiter

🤝 B2B

🏢 Enterprise

Recruitment • B2B • Enterprise

BrightSide is an Argentina-based IT staffing and SAP consulting company that helps organizations build and augment technology project teams by sourcing senior, specialized IT talent and providing end-to-end SAP services. They offer IT staff augmentation, recruiting and hunting, on-site or remote assignments, and various SAP services including implementations and migrations to S/4HANA, ABAP and Fiori/UI5 development, integrations, SAP BASIS and security, and packaged support and maintenance plans. BrightSide focuses on rapid delivery, flexible engagement models, and long-term support for enterprise clients.

📋 Description

• 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

🎯 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 • 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.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible working hours • Paid time off • Professional development opportunities