Job Title: Full Stack AI Engineer

Company Name: Create Music Group

Job Details: $120k-$150k/yrRemoteFull,Time

Job Url: https://hiring.cafe/viewjob/dowjeqomjn95nsyf

Job Description: Posted 1w agoFull Stack AI Engineer@ Create Music GroupView All JobsWebsiteCanada$120k-$150k/yrRemoteFull TimeResponsibilities:Design, build, and maintain modular AI agents that automate multi-step workflows across CreateOS, Own RAG pipelines, retrieval architectures, and semantic search systems grounded in CreateOS's data, Implement guardrails, evaluation frameworks, and human-in-the-loop controls for agentic systemsRequirements Summary:5+ years software engineering; hands-on in agentic AI workflows; strong frontend (React/Next.js) and backend (Python/Node.js); integrate LLMs; design RESTful APIs; work with RAG, vector stores, and AI pipelines.Technical Tools Mentioned:Frontend: React, Next.js, TypeScript, Tailwind CSS, Backend: Python, FastAPI, Node.js, AI & Agent Frameworks: LangChain, LangGraph, DeepEval, MCP, Vector & Retrieval: Pinecone, Weaviate, Databases & APIs: PostgreSQL, Snowflake, RESTful API design, Infrastructure: Docker, Kubernetes, GCP, AWS, Supabase, Collaboration & Dev Tools: GitHub, Linear, Cursor, Claude Code
Job SummaryWe are building CreateOS — a next-generation operating system for modern record labels — and AI is at the center of it. As a Full Stack AI Engineer, you will own the end-to-end design and delivery of AI-powered features that make CreateOS intelligent. This means building the agentic workflows, APIs, and interfaces through which users interact with AI copilots, predictive tools, and automated pipelines — from first concept to production deployment.This is a high-ownership role for someone who thinks in full systems. You won't hand work off at the API boundary — you'll own the experience from the data layer to the UI. You will work directly with the VP of AI & ML Engineering and sit at the intersection of product, engineering, and applied AI. Your immediate impact will be on three of CMG's highest-priority AI initiatives: M&A catalog valuation tooling, AI-driven A&R discovery surfaces, and marketing automation agents — each directly tied to revenue growth and competitive differentiation.You'll work in close collaboration with the ML Engineer, who owns the intelligence layer (models, features, evaluation). You own the application and orchestration layer that brings that intelligence to users.ResponsibilitiesAgentic AI & LLM Systems (Primary Ownership)Design, build, and maintain modular AI agents that automate multi-step workflows across CreateOS (contracts, accounting, distribution, metadata)Own RAG pipelines, retrieval architectures, and semantic search systems grounded in CreateOS's structured business data (contracts, royalty statements, catalog metadata, etc.)Implement guardrails, evaluation frameworks, and human-in-the-loop controls for agentic systemsIntegrate LLMs (OpenAI, Anthropic, or open-source models) into user-facing features across CreateOS modulesFull Stack DevelopmentDesign, build, and maintain scalable, production-grade applications across the frontend and backendBuild intuitive, AI-native user experiences including chat interfaces, copilot-style tools, and workflow automation surfaces within CreateOSOwn features end-to-end — from data modeling and API design to UI implementation and deploymentPlatform & InfrastructureDeploy and maintain services using containerization and cloud platformsEnsure AI-powered features are reliable, observable, and performant in productionCollaborate with the ML Engineer to integrate model outputs and feature pipelines cleanly into product surfacesMaintain high code quality standards through unit and integration testing, code reviews, and CI/CD pipeline ownershipPartner with Data Engineering (who owns pipeline infrastructure) to consume and integrate internal data pipelines (dbt, Airflow), third-party API feeds (DSPs, distributors), webhook and event-driven data flows, and ETL outputs into CreateOS product surfacesIteration & Product ThinkingRapidly prototype and evaluate new AI-powered features based on internal user feedbackContribute to technical architecture decisions with a bias toward shipping and learningCommunicate tradeoffs clearly across engineering, product, and business stakeholdersOther duties as assignedQualifications 5+ years of software engineering experience with a track record of shipping production applicationsHands-on experience building and owning agentic or multi-step AI workflows in productionStrong proficiency in a modern frontend framework (React, Next.js) and a backend language (Python or Node.js)Hands-on experience integrating LLMs or AI APIs into user-facing productsFamiliarity with RAG systems, vector databases, and embedding-based retrievalExperience designing and documenting RESTful APIsProficiency in relational databases (PostgreSQL or similar); comfortable writing and optimizing SQL queriesSolid understanding of Kubernetes, containerization (Docker), and DevOps practices — including CI/CD pipelines, observability, and deployment workflowsExperience with AI evaluation practices — LLM output quality assessment, hallucination detection, and building eval frameworks for agentic systemsProficiency with AI-native development tools (Cursor, Claude Code, or similar)Ability to work independently and own features from concept to deploymentPreferred QualificationsPrevious experience at a startup or as an early/founding engineerPortfolio of personal or professional AI projects — RAG systems, LLM agents, copilot-style tools (GitHub links welcome)Familiarity with the music industry, rights management, or royalties workflowsExperience with AI-native development tools (Cursor, Claude Code, or similar)Knowledge of data privacy, compliance, and responsible AI deployment considerationsTech StackFrontend: React, Next.js, TypeScript, Tailwind CSSBackend: Python (FastAPI), Node.jsAI & Agent Frameworks: LangChain, LangGraph, DeepEval, MCPVector & Retrieval: Pinecone, Weaviate, or similarDatabases & APIs: PostgreSQL, Snowflake, RESTful API designInfrastructure: Docker, Kubernetes, GCP or AWS, SupabaseCollaboration & Dev Tools: GitHub, Linear, Cursor / Claude CodePay Scale$120,000 - $150,000 CAD per yearThe final compensation within this range will be determined based on the candidate’s experience, skills, and overall fit for the role.