AI Architect

Salesforce•San Francisco, CA

1d•$218,400 - $401,400•Hybrid

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Are you passionate about the cutting edge of Artificial Intelligence and eager to shape the future of intelligent solutions within Salesforce? We're growing a dynamic team dedicated to exploring, developing, and integrating generative AI and applied AI technologies across our products and operations. This is a unique opportunity to lead and contribute to innovative projects that will redefine how our internal teams leverage AI to enhance productivity, drive insights, and create new capabilities.

Requirements

At least 15 years of programming and architectural experience.
Strong proficiency in Python and relevant AI/ML frameworks.
Knowledge of various machine learning models, including deep learning architectures, particularly those related to natural language processing (NLP) and generative models.
Solid understanding of cloud platforms, specifically AWS, and MLOps principles.
Familiarity with core AI/ML concepts, including data preprocessing, feature engineering, model training, evaluation, and deployment.
Practical experience working with Large Language Models (LLMs), fine-tuning, prompt engineering, and understanding their applications for text generation, summarization, code generation, and conversational AI. Capable of reading through AI research and understanding approaches for how to apply new concepts.
A strong understanding of developing and delivering services on cloud platforms like AWS, including concepts around cloud security, identity and access management, data protection, and network security.
Hands-on experience designing, integrating, or utilizing autonomous AI coding agents and developer platforms (such as Salesforce Agentforce) to streamline software development lifecycles, automate workflow execution, and enhance developer productivity.
Strong verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders and providing content that can be understood by both humans and models.
Proven ability to work effectively in a collaborative, fast-paced team environment where requirements are light and ambiguity is high. Must be capable of leading through the ambiguity and into durable solutions.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.

Nice To Haves

Experience with Salesforce platform technologies (specifically Apex, Agentforce, and Data Cloud).
Prior experience in a leadership or mentorship role within an engineering development team.
Familiarity with data governance, security, and privacy best practices in an enterprise context.

Responsibilities

Contribute to the strategic direction for generative AI and applied AI initiatives within Salesforce, identifying high-impact areas for innovation and development.
Lead the design, development, and deployment of generative AI and applied AI prototypes and production-ready solutions. This includes leveraging LLMs for code generation, content creation, intelligent search, data synthesis, and more.
Stay abreast of the latest advancements in generative AI, applied AI, and machine learning research and techniques, both from within Salesforce’s own product suite as well as emerging industry tools and research papers. Evaluate new models, tools, and platforms for their potential application within Salesforce.
Partner with product managers, data scientists, engineers, and business stakeholders to gather requirements, define project scopes, and ensure successful integration and adoption of AI solutions.
Act as a subject matter expert, providing guidance and sharing knowledge with other teams on best practices, ethical considerations, and the capabilities of generative and applied AI.
Monitor and optimize the performance of deployed AI models, ensuring scalability, reliability, and continuous improvement.