Principal Architect, AI Labs

Salesforce•San Francisco, CA

About The Position

Salesforce AI Labs is seeking a deeply technical, product-savvy AI architect to support potential acquisitions and strategic investments and to help accelerate companies after acquisition. The role provides independent, hands-on technical depth during M&A or investment diligence and helps develop shared DeepTech capabilities, models, and infrastructure that portfolio companies can use after joining AI Labs. The Principal Architect will evaluate AI technology, teams, and intellectual property, identify technical risks and opportunities, and provide clear recommendations to AI Labs leadership. Across the portfolio, the role will advise on shared technologies, evaluation frameworks, infrastructure, standards, and services where they create material leverage, while avoiding becoming a centralized bottleneck. Formal diligence experience is not required.

Requirements

Principal- or Distinguished-level engineering or architecture experience in AI, including basic and applied AI, ML, and production-scale AI products.
Deep understanding of modern AI architectures, models, training and post-training, inference, data, evaluation, infrastructure, production systems, and how technical choices shape product outcomes.
Ability to rapidly understand unfamiliar technical stacks and distinguish true technical differentiation from implementation detail.
Experience working with startup- or founder-led engineering teams.
Strong technical judgment combined with deep product taste and pragmatic business thinking.

Nice To Haves

Experience with technical diligence, DeepTech investing, acquisitions, or startup evaluation; however, having shipped differentiated AI/ML products matters more.

Responsibilities

Lead technical and AI diligence for potential acquisitions and strategic investments.
Test, study, use, and remix technology to evaluate architecture, models, data strategy, infrastructure, security, scalability, technical differentiation, and technical debt.
Interview and score DeepTech talent.
Assess build-versus-buy questions and the defensibility of a company's technology, team, and intellectual property.
Partner directly with founders, CTOs, and engineering leaders during diligence.
Identify material technical risks and opportunities and translate them into clear recommendations for AI Labs leadership.
Identify opportunities for portfolio companies to adopt shared AI technologies, evaluation frameworks, infrastructure, standards, and services when doing so creates material leverage.
Identify capabilities that should be built once across AI Labs rather than repeatedly by individual companies, and assess the associated technical and nontechnical tradeoffs.
Serve as a senior technical advisor across the AI Labs portfolio without becoming a centralized bottleneck.