Artificial Intelligence Developer

Urban Ridge Supplies; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

BrainRidge Consulting is seeking experienced AI Developers to build Generative AI agents, retrieval systems, and intelligent workflows for enterprise clients. You will work on modern AI applications, integrating AI with data, tools, and APIs to deliver production-ready solutions.

The role requires hands-on software engineering with AI expertise, knowledge of LLMs, AI frameworks, and cloud/DevOps practices, delivering secure, scalable production systems.

Qualifications

• 3+ years of hands-on software engineering experience with AI-powered applications.
• Proven experience building AI agents, agentic workflows, and retrieval solutions.
• Hands-on experience with LLMs and foundation models (OpenAI, Anthropic, Google, etc.).

Responsibilities

• Build Generative AI, AI agents, and intelligent workflows for clients.
• Develop AI agents that reason over enterprise data and execute multi-step workflows.
• Integrate AI apps with enterprise platforms, APIs, and data stores.
• Deploy AI workloads with cloud platforms, containers, and CI/CD.

Skills

Problem solving

Communication

Team collaboration

Tools

Python

JavaScript/TypeScript

APIs

SQL

Git

LangChain/LangGraph

LlamaIndex

Semantic Kernel

Docker

Kubernetes

CI/CD

Infrastructure as Code

MLflow

LangSmith

Langfuse

Job description

BrainRidge Consulting is a premium FinTech Technology Consulting firm with the energy of a startup and the experience of an enterprise. With a mission to empower financial institutions and organizations to thrive in the digital age, we provide cutting‑edge technology solutions and strategic guidance to drive innovation and growth. As we continue to grow, we are seeking motivated and experienced AI Developers to join our team.

As an AI Developer, you will build and produce modern AI applications, agents, and intelligent workflows for our clients. This is a hands‑on engineering role for someone who combines strong software engineering fundamentals with deep AI expertise and can take solutions from prototype to secure, scalable production. This role is ideal for someone who thrives at the intersection of software engineering, applied AI, and enterprise integration, with a strong understanding of how AI drives business outcomes.

Key Responsibilities

• Build Generative AI, AI agent, agentic workflow, enterprise search & retrieval, and intelligent automation solutions for clients.
• Develop AI agents that reason over enterprise data, use tools and APIs, maintain state, and execute multi-step workflows.
• Build RAG and agentic retrieval solutions across documents, databases, APIs, search platforms, and enterprise systems.
• Develop workflows using tool/function calling, structured outputs, memory, context engineering, and human‑in‑the‑loop controls.
• Integrate AI applications with enterprise platforms, SaaS products, APIs, databases, and systems of record.
• Build reusable AI services, APIs, components, SDKs, and accelerators.
• Implement hybrid search, semantic retrieval, reranking, query rewriting, and knowledge access patterns.
• Build multimodal AI solutions using text, documents, images, audio, and other enterprise content.
• Implement AI evaluation, regression testing, guardrails, and quality controls.
• Instrument AI applications for tracing, observability, latency, token usage, cost, and agent behavior.
• Implement controls for prompt injection, data leakage, unsafe tool execution, and excessive agent permissions.
• Deploy AI workloads using cloud platforms, containers, CI/CD, and modern DevOps practices.
• Partner with architects, engineers, and business stakeholders to translate AI use cases into production‑ready solutions.

Qualifications

• 3+ years of hands‑on software engineering experience, with meaningful experience building and shipping AI-powered applications.
• Strong hands‑on experience with Python, JavaScript/TypeScript, APIs, SQL, and Git.
• Proven experience building AI agents, agentic workflows, and RAG or agentic retrieval solutions.
• Hands‑on experience with LLMs and foundation models, such as OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, Cohere, or open‑source models.
• Experience with AI frameworks such as LangChain/LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or Model Context Protocol (MCP).
• Experience with embeddings, semantic and hybrid search, reranking, and model routing and orchestration.
• Familiarity with search and vector platforms such as PostgreSQL/pgvector, Elasticsearch/OpenSearch, Azure AI Search, Pinecone, Qdrant, Weaviate, Redis, or Neo4j.
• Hands‑on experience with at least one major cloud platform (Azure, AWS, or Google Cloud) and its AI services.
• Experience with Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Familiarity with AI observability and evaluation tools such as MLflow, LangSmith, Langfuse, or Arize Phoenix.
• Strong understanding of AI security practices, including prompt injection, data leakage, and agent permission controls.
• Excellent communication and problem‑solving skills, with the ability to take AI solutions from prototype to production.