AI Integration Engineer — Multimodal AI Platform - Freelance

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 Strong 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

The engineer will build and orchestrate a multimodal AI platform integrating vision, speech, and language models via standardized interfaces. They will design vendor-agnostic abstraction layers to ensure models are swappable and observable within a production-grade human review workflow.

Requires over 6 years of software engineering experience with a proven track record of integrating AI/ML services and LLMs into production. Candidates must be based in Canada and proficient in Python and cloud AI provider SDKs.

• PythonPreferred

Identified from the job description. Confirm important requirements above.

• AI Integration
• Python
• LLM Orchestration
• RAG
• Computer Vision
• Speech-to-Text
• Model Context Protocol
• API Integration
• Software Architecture
• Data Engineering
• Cloud AI Services
• MLOps
• Vendor-agnostic Abstraction
• Function Calling
• Multimodal AI

• Software
• Technology
• Engineering
• Data & Analytics
• Science & Research

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level