Data & AI Principal
Job Description | Faye
About Faye
Faye is a fast-growing, award-winning team on a mission to make the best software in the world even better. They customize, implement, and manage industry-leading sales, service, marketing, and AI solutions for ambitious mid-market and enterprise companies. An Inc. 5000 winner 10 years running, headquartered in California, and operating across 4 continents. Award-winning partner of SugarAI, Salesforce, Intercom, Zendesk, HubSpot, and more — Faye doesn't just deploy software, they own it, improve it, and build on top of it.
The Role
As a Data & AI Principal at Faye, you will be the primary builder responsible for executing the most complex, high-impact AI initiatives. This is a senior, hands-on-keyboard role — you won't just architect systems on a whiteboard. You will own the development of agentic workflows, RAG pipelines, and data integrations that drive 10x productivity for clients.
You will act as the lead technical expert during project lifecycles, a hands-on mentor to client engineering teams, and the core developer of AI solutions that make the world's best software even better.
Daily Tasks & Responsibilities
End-to-End Project Execution: Directly build, test, and deploy production-ready AI agents and workflows using Python and frameworks like LangChain, LangGraph, or CrewAI. Own the technical implementation from kickoff to delivery.
Solution Architecture & Implementation: Design and build robust RAG systems, configure vector databases (Pinecone, Weaviate, etc.), and implement scalable, secure model integrations focused on efficiency and reliability.
Technical Scoping & Collaboration: Work closely with client stakeholders to translate business challenges into clear technical requirements and a concrete project plan. Lead technical discovery to define what is buildable and how.
Performance Optimization & Observability: Monitor, debug, and enhance model performance. Implement tooling (Arize, Weights & Biases) to track and mitigate hallucinations, data drift, and performance bottlenecks.
Technical Handover & Enablement: Empower clients through clear documentation, code walkthroughs, and implementation support so they can effectively operate and maintain the solutions built.
Technical Authority: Serve as the go-to expert for agentic AI implementation, guiding best practices in system design, security, and scalability across all projects.
Required Technical Skills
Core AI Literacy: Mastery of LLM fundamentals (OpenAI, Claude, Gemini, etc.), Generative AI, and Neural Networks.
Python Proficiency: Strong ability to write clean, efficient, production-ready Python across the modern AI software stack.
Model Training Knowledge: Deep understanding of Supervised, Unsupervised, and Reinforcement Learning trade-offs.
Vector Database Expertise: Hands-on experience with Pinecone, Weaviate, Milvus, or pgvector — including high-dimensional embeddings and efficient chunking strategies.
RAG & Orchestration: Proven experience building Retrieval-Augmented Generation architectures from scratch.
Connectivity Standards: Familiarity with the Model Context Protocol (MCP) for linking tools and data sources securely.
Hardware Awareness: Understanding of GPU vs. CPU trade-offs for parallel computing and model inference.
Preferred Skills & Tooling
Frameworks & Scaling
Experience with PyTorch/TensorFlow or managing models via HuggingFace.
Familiarity with Ray, Kubeflow, or MLFlow for scaling and experiment tracking.
AI Infrastructure
AI Gateways: Experience with OpenRouter, LiteLLM, or Bifrost for multi-model API management.
Managed Platforms: Exposure to AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
Agent & Workflow Tools
Agent Management: Hands-on experience with CrewAI, n8n, or Flyte.
No-Code/Low-Code: Proficiency with Zapier, Tray.io, or Workato for connecting AI to existing business workflows.
Enterprise AI: Experience with platforms like Glean or Moveworks, or CRM-native AI (Agentforce, Zendesk Advanced AI, Intercom Fin).
Soft Skills & Professional Attributes
The "Teacher" Mindset: Ability to explain complex topics clearly to non-technical stakeholders.
Adaptability: Proven track record of self-teaching and rapidly adopting new tools as the AI landscape evolves.
Problem Solver: Goes beyond fixing bugs to finding architectural bottlenecks and suggesting more efficient approaches.
Logistics
Work Environment: 100% remote. Must be comfortable working across time zones with high self-accountability.
Travel: 15–25% travel for on-site client workshops, project kickoffs, and internal team summits.
Equipment: Faye provides a modern tech stack and necessary hardware/software subscriptions, including proper AI tools.
Benefits: Comprehensive medical, dental, and vision benefits, plus 401k with matching.
Our Values
Anything is Possible
Move Fast
Take Care of Our Clients
Growth Mindset
Own What Happens
Conscious & Enthusiastic Teamwork
Innovate
Prepared by Lupa Hire | Confidential