Fractional AI Strategy Advisor + Infrastructure Consultant (Python/LangGraph/Docker)
Description
Role Overview
We are seeking a senior AI strategy advisor for a solo financial advisory practice. This is a fractional, long-term advisory engagement — not a project-based contract. You will serve as a trusted technical advisor and occasional hands-on implementer, working directly with the founder/architect.
The practice runs a local Docker-based AI infrastructure (13 containers, 5 profiles) built on LangGraph workflows, PydanticAI agents, LiteLLM multi-model routing, MCP (Model Context Protocol) bridges, Graphiti knowledge graph (FalkorDB), and RAGFlow document search. The system operates under FINRA compliance requirements with fail-closed PII redaction.
What You Will Do
- Advise on architecture decisions, tool selection, and AI/LLM best practices as the landscape evolves - Guide implementation of new capabilities — you know how to do things that would take the founder hours of research - Review and improve existing LangGraph workflows and PydanticAI agent designs - Recommend and evaluate new frameworks, models, and orchestration patterns - Occasionally implement features hands-on when advisory alone is not enough - Help with operations and maintenance — upgrades, monitoring, infrastructure care
Required Skills
- Deep expertise in the AI/LLM ecosystem — frameworks, models, orchestration patterns - Strong Python skills (FastAPI, async, LangGraph SDK, PydanticAI) - Docker Compose and self-hosted infrastructure experience (NOT cloud-only) - Ability to track the fast-moving AI landscape and translate trends into actionable guidance - Excellent communication — you can explain complex technical tradeoffs clearly
Strong Plus
- LangGraph production experience - MCP (Model Context Protocol) — building or consuming MCP servers - Knowledge graphs (Graphiti, FalkorDB, Neo4j) - RAG pipeline design and optimization - Multi-model routing (LiteLLM or similar) - Experience advising solo practitioners or small teams (vs. enterprise)
Engagement Model
- Fractional, ongoing — approximately 10-15 hours/week - Month-to-month, flexible working style (async, sync, pair sessions) - Remote, any timezone - You are the expert advisor; the founder is the architect and decision-maker
Skills
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