Full-time

Remote (with preference for San Francisco, CA or New York, NY based candidates)

Tribe AI is looking for a talented Solutions Architect to lead our Sales team to incubate, pilot, and deploy custom Generative AI technologies with our clients. In this role, the Solutions Architect will play a key role in identifying practical use cases and applications for advanced AI technologies and supporting the sales team by providing technical expertise in cutting-edge AI solutions. This will involve close collaboration with clients to understand and scope AI-driven solutions in real-world scenarios.‍

Key responsibilities:

• Help clients understand which problems to solve with AI and how to solve them from a technical perspective
• Advise the sales team and client on technical complexity and scope of projects
• Ensure we are building production-oriented AI products that add business value whenever we can
• Provide technical guidance and ensure we are leveraging Tribe AI’s internal products wherever possible
• Aggregate insights from client needs to inform our sales strategy and internal product development
• Collaborate in scoping tools and methodologies for mid-market and enterprise AI applications
• Communicate and design reference architectures and solution frameworks that scale across projects

Qualifications:

• MSc in Computer Science, Software Engineering, ML Engineering, or related fields, or equivalent experience.
• 5+ years of experience in ML model development and deployment
• Experience developing production LLM powered applications and tools with natural language interface at scale
• Excellent communication and presentation skills to collaborate with clients and internal Tribe AI team members
• Excellent proficiency in Python and familiarity with ML frameworks like PyTorch or TensorFlow.
• Excellent practical knowledge of Generative AI and the ever-evolving LLM ecosystem.

Ways to stand out from the crowd:

• Experience in customer facing roles and the ability to scope projects and estimate required effort to build end-to-end applications
• Ability to train BERT, GPT, and other open source language and ML models
• Experience with information retrieval systems and RAG applications
• Familiarity with MLOps life cycle and experience with LLM Ops workflows
• Expertise with production cloud infra on AWS, Azure, and GCP