Fractional AI Architect (Consultant)

Generative AI, ML Systems & Scalable Platform Architecture

Contract / Fractional Engagement Remote

Overview

Bridge-it.ai An AI-driven SaaS platform operating in the career readiness and education technology space is seeking a Fractional AI Architect to conduct an architecture review and provide technical guidance for the platform's AI and data systems.

Experience in the U.S. K-12 education ecosystem or EdTech platforms is highly desirable, particularly in systems that support students, educators, counselors, or workforce readiness initiatives.

The platform combines Generative AI copilots, retrieval-augmented generation (RAG), knowledge graphs, and traditional machine learning models to support career exploration, pathway planning, and personalized recommendations for students.

The engagement focuses on conducting a structured architecture audit and evaluating whether the current system design aligns with the platform's long-term goals for scalability, reliability, observability, and continuous improvement.

The consultant will collaborate with engineering and product leadership to identify architectural gaps and provide recommendations for strengthening the AI platform.

This role is intended for senior AI architects or principal-level engineers who have previously designed and operated production AI systems at scale.

Scope of Engagement

The consultant will review the current system architecture and provide recommendations across several key areas.

AI Platform Architecture Review

Conduct a structured audit of the platform's AI architecture, including:

generative AI copilot design
agentic workflow orchestration
retrieval-augmented generation pipelines
knowledge retrieval systems
vector database usage
knowledge graph integration
context management and AI memory strategies
prompt and instruction architecture

Assess whether the current design supports:

reliable AI behavior
scalable inference
controllable AI workflows
maintainable system architecture.

Generative AI & LLM Systems

Evaluate the architecture and technical strategy related to:

LLM model selection
API-based vs self-hosted model strategies
embeddings and vector search pipelines
prompt and context engineering
RAG architecture
agent orchestration frameworks
guardrails and reliability mechanisms.

Provide recommendations to improve:

model response quality
latency
cost efficiency
system reliability.

Traditional Machine Learning Systems

Review architecture related to traditional ML use cases such as:

recommendation systems
predictive analytics
forecasting models
clustering and segmentation pipelines.

Assess the architecture supporting:

training pipelines
experimentation workflows
model deployment
model lifecycle management.

Copilot Interaction & Agentic Workflows

Evaluate the design of AI-driven workflows supporting the copilot experience, including:

user-initiated interactions
event-driven AI recommendations
multi-step reasoning workflows
recommendation pipelines.

Provide guidance on improving:

intent detection
workflow orchestration
AI reasoning pipelines
reliability and safety mechanisms.

Platform Architecture & System Design

Assess the platform's core architecture, including:

microservices architecture
event-driven system design
message-based communication patterns
API architecture
service boundaries and modularity.

Review the application of architectural patterns such as:

event-driven architecture
message-driven systems
asynchronous processing
hexagonal / ports-and-adapters architecture.

Provide recommendations for improving:

scalability

Fractional AI Architect (Consultant)

Contract / Fractional Engagement Remote

Overview

Scope of Engagement

AI Platform Architecture Review

generative AI copilot design

agentic workflow orchestration

retrieval-augmented generation pipelines

knowledge retrieval systems

vector database usage

knowledge graph integration

prompt and instruction architecture

reliable AI behavior

scalable inference

controllable AI workflows

maintainable system architecture.

Generative AI & LLM Systems

LLM model selection

embeddings and vector search pipelines

prompt and context engineering

RAG architecture

agent orchestration frameworks

guardrails and reliability mechanisms.

Provide recommendations to improve:

model response quality

latency

cost efficiency

system reliability.

Traditional Machine Learning Systems

recommendation systems

predictive analytics

forecasting models

clustering and segmentation pipelines.

Assess the architecture supporting:

training pipelines

experimentation workflows

model deployment

model lifecycle management.

Copilot Interaction & Agentic Workflows

user-initiated interactions

event-driven AI recommendations

multi-step reasoning workflows

recommendation pipelines.

Provide guidance on improving:

intent detection

workflow orchestration

AI reasoning pipelines

reliability and safety mechanisms.

Platform Architecture & System Design

microservices architecture

event-driven system design

message-based communication patterns

API architecture

service boundaries and modularity.

event-driven architecture

message-driven systems

asynchronous processing

Provide recommendations for improving:

scalability

Fractional AI Architect (Consultant) at Bridge-it