Principal Artificial Intelligence Architect

Fractal Analytics•California, CA

2d•$0 - $235,000•Onsite

About The Position

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Requirements

8+ years of overall experience with a minimum of 4 years in production GenAI / LLM systems (shipped, maintained, and scaled — not prototype or research)
Deep expertise in LLM orchestration frameworks — LangChain, LangGraph, LlamaIndex, or equivalent agentic systems
Strong Python proficiency; solid backend engineering fundamentals including REST API design, async patterns, and containerized deployment
Sufficient fluency in data science, ML, and BI concepts to reason about analytical accuracy, data quality, and the reliability of model outputs
Demonstrated ability to work in fast-moving, ambiguous environments where requirements evolve and scope is not always fixed at the start
Strong first-principles thinking — able to evaluate trade-offs, challenge assumptions, and design systems that are defensible and modular
US-based; PST or MST timezone required (Sunnyvale / Bay Area strongly preferred)

Nice To Haves

Hands-on experience with Model Context Protocol (MCP) or building on agent-native enterprise platforms
Background in analytics, BI, or data product development — understanding the domain where AI meets enterprise reporting and decision-making
Prior experience in a consulting or client-embedded delivery model, operating in matrixed organizations with distributed teams
Certifications in LLM or cloud AI platforms (AWS Bedrock, Azure OpenAI, Anthropic / Claude, Google Vertex AI, etc.)
Experience with LLMOps tooling — LangSmith, MLflow, Weights and Biases, or equivalent

Responsibilities

Design and deploy RAG pipelines, multi-agent architectures, and LLM-powered analytics or decision-support workflows
Work in fast-moving, ambiguous environments where requirements evolve and scope is not always fixed at the start
Evaluate trade-offs, challenge assumptions, and design systems that are defensible and modular