Negotiable
Outside
Remote
USA
Summary: The Salesforce AI/ML Technical Architect role focuses on leading the design and development of AI-driven systems within the Salesforce ecosystem. The position requires expertise in data strategy, AI/ML implementation, and providing technical guidance to engineering teams. The architect will also be responsible for ensuring responsible AI practices and improving automation across services. This is a long-term remote position based in the USA.
Key Responsibilities:
- Lead the design and development of scalable, performant AI-driven systems and architecture within the Salesforce ecosystem.
- Define and manage complex data landscapes, including data strategies and efficient data processing pipelines for AI applications.
- Drive the implementation of AI and machine learning models and algorithms using frameworks like Tensor Flow or PyTorch.
- Design, build, and maintain solutions that integrate AI capabilities into the Salesforce platform.
- Provide technical leadership and mentorship to engineering teams on software development and AI best practices.
- Analyze and mitigate risks in AI models to enhance explainability and user trust.
- Lead initiatives to improve capacity visibility and automation across various services.
Key Skills:
- Expertise in Salesforce platform, including tools like Apex, LWC, and Data Cloud.
- Proficiency in AI/ML frameworks such as Tensor Flow or PyTorch.
- Strong understanding of data strategies and complex data models.
- Experience in implementing AI-driven systems and architectures.
- Ability to provide technical guidance and mentorship to teams.
- Knowledge of responsible AI practices and risk mitigation.
- Skills in automation and improving system capacity.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Role:Salesforce AI/ML Technical Architect
Location: Remote
Duration: Longterm
Architectural Design & Leadership: Lead the design and development of scalable, performant AI-driven systems and architecture within the Salesforce ecosystem, often leveraging Large Language Models (LLMs) and AI agents.
Data Strategy: Define and manage complex data landscapes, including data strategies, sophisticated data models, and efficient data processing pipelines for AI applications.
AI/ML Implementation: Drive the implementation of AI and machine learning models and algorithms using frameworks like Tensor Flow or PyTorch and tools like Cursor or W&B.
Salesforce Platform Expertise: Design, build, and maintain solutions that integrate AI capabilities into the Salesforce platform, utilizing tools like Apex, LWC, and Data Cloud.
Team & Technical Guidance: Provide technical leadership and mentorship to engineering teams on software development, AI best practices, and complex system integration.
Responsible AI & Trust: Analyze and mitigate risks in AI models, contributing to the development and adoption of tools that enhance explainability and user trust, as highlighted by companies like Salesforce.
Automation & Capacity: Lead initiatives to improve capacity visibility and automation across various services, building resilient and automated systems.