Location: Fully remote (Canada) Duration: Milestone-based contract

Overview A large-scale organization is building a next-generation multimodal AI platform to process vast volumes of imagery, video, and audio. The platform will perform first-pass analysis using computer vision, speech-to-text, and language models, then route findings to human experts for review and approval. This is a software architecture, integration, and data-engineering effort that assembles best-in-class existing AI services into one robust production platform — not a model-building project.

The role requires a senior, hands-on engineer who has shipped similar systems and can make AI models swappable, observable, and production-grade.

Key Responsibilities

- Build integrations for vision, speech-to-text, and LLM services behind clean, standardized, swappable interfaces
- Design and implement orchestration for sequential and parallel multimodal workflows, including running multiple providers for the same task and hot-swapping models with configuration changes
- Implement Model Context Protocol (MCP) support so external agents and tools can plug in
- Wire AI output (metadata, transcripts, summaries, confidence scores) into the human review flow
- Capture workflow status, metrics, and evaluation signals
- Design vendor-agnostic abstraction layers so underlying models can be replaced without touching the application

Required Qualifications





- 6+ years in software engineering with a track record integrating AI/ML services via APIs into production
- Hands-on LLM integration experience (RAG, function/tool calling, orchestration frameworks)
- Computer-vision or speech-to-text integration experience, ideally both in one system
- Experience designing vendor-agnostic abstraction layers for model replacement
- Solid Python skills and proficiency with relevant AI SDKs
- Fluency across cloud AI providers
- Portfolio or references demonstrating prior work that closely mirrors multimodal-integration scope

Preferred Qualifications

- Experience with Model Context Protocol (MCP)
- Experience with evaluation/MLOps tooling and automated model-quality checks
- Experience with cloud AI services (AWS Rekognition/Transcribe/Bedrock, Azure AI, GCP Vertex/Vision/Speech)
- Experience building retrieval pipelines over large document or media stores
- Experience delivering complex software systems for government or regulated industries

Work Location & Requirements

- Fully remote position
- Must be based in Canada
- Must be able to contract as an independent professional in Canada
- Freelance/independent contractor engagement (not employment)
- Selection process includes review of background and past work, followed by a short technical assessment/coding exercise

📌 AI Integration Engineer — Multimodal AI Platform - Freelance (Canada)
🏢 CrowdPlat
📍 Canada