AI Architect
- Moncton, NB, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 7+ years of experience in software or solutions architecture, including meaningful experience architecting AI or machine learning systems.
- Posting language
- English
- Posted
Original job description
Location: Maritimes (New Brunswick, Prince Edward Island, Nova Scotia) (Hybrid)
About BrainRidge
BrainRidge Consulting is a premium FinTech Technology Consulting firm with the energy of a startup and 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 a motivated and experienced AI Architect.
Role Overview
We are seeking an AI Architect to design and build enterprise-grade AI solutions, platforms, and agentic systems for our clients. This role sits at the intersection of AI, software architecture, cloud, data, security, and enterprise technology, working with business and engineering teams to turn complex AI use cases into scalable, secure, production-ready solutions. It is ideal for someone who goes beyond demos and prompt engineering and understands how to architect AI systems that operate reliably inside large enterprises. Our Maritimes office is located in Moncton, New Brunswick. This role offers a flexible hybrid arrangement, with occasional in-office days as needed.
Key Responsibilities
At BrainRidge Consulting, we value and prioritize diversity, equity, and inclusion. We believe that a diverse and inclusive workplace leads to a more innovative and productive team. We welcome applicants of all backgrounds and are committed to providing a safe, fair, and welcoming environment where everyone feels valued and respected. If you require accommodations during the hiring process, please let us know.
About BrainRidge
BrainRidge Consulting is a premium FinTech Technology Consulting firm with the energy of a startup and 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 a motivated and experienced AI Architect.
Role Overview
We are seeking an AI Architect to design and build enterprise-grade AI solutions, platforms, and agentic systems for our clients. This role sits at the intersection of AI, software architecture, cloud, data, security, and enterprise technology, working with business and engineering teams to turn complex AI use cases into scalable, secure, production-ready solutions. It is ideal for someone who goes beyond demos and prompt engineering and understands how to architect AI systems that operate reliably inside large enterprises. Our Maritimes office is located in Moncton, New Brunswick. This role offers a flexible hybrid arrangement, with occasional in-office days as needed.
Key Responsibilities
- Design end-to-end architectures for Generative AI, Agentic AI, RAG, machine learning, and intelligent automation solutions, translating business requirements into scalable technical approaches.
- Architect AI agents, including their tools, workflows, memory, permissions, context, and human-in-the-loop controls.
- Design enterprise AI platforms and reusable capabilities, including model gateways and catalogues, agent runtimes and registries, RAG and knowledge services, prompt and tool registries, and evaluation and observability platforms.
- Define guardrails, governance, usage monitoring, and cost controls for enterprise AI systems.
- Evaluate and recommend AI models based on capability, latency, security, cost, and use-case requirements.
- Design retrieval and knowledge architectures across structured and unstructured enterprise data, and integrate AI solutions with enterprise applications, APIs, databases, and systems of record.
- Define AI security patterns covering identity, authorization, data protection, prompt injection, tool execution, and agent permissions.
- Establish architecture patterns and deployment strategies for AI evaluation, observability, testing, and production operations across cloud, hybrid, serverless, and Kubernetes environments.
- Develop reusable AI reference architectures, standards, accelerators, and decision frameworks, and lead architecture workshops, discovery sessions, and proofs of concept.
- Provide technical leadership to AI, software, data, and platform teams, and partner with security, data, cloud, risk, privacy, and business stakeholders.
- 7+ years of experience in software or solutions architecture, including meaningful experience architecting AI or machine learning systems.
- Strong experience across generative and agentic AI, including LLMs, RAG, multi-agent systems, tool/function calling, context engineering, AI memory, and model routing.
- Experience with AI frameworks such as LangChain/LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or MCP, and model ecosystems such as OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, or Cohere.
- Strong experience with at least one major cloud platform (Azure, AWS, or Google Cloud) and its AI services.
- Experience with data and knowledge architecture, including SQL/NoSQL databases, data lakes and warehouses, vector databases, hybrid/semantic search, and knowledge graphs.
- Strong understanding of enterprise architecture, including distributed systems, microservices, REST APIs, event-driven architecture, Kubernetes, serverless computing, and identity and access management.
- Hands-on experience with Python, SQL, APIs, Git, CI/CD, Docker, Kubernetes, and Infrastructure as Code.
- Familiarity with MLOps/LLMOps/AgentOps practices and observability tools such as MLflow, LangSmith, Langfuse, Arize Phoenix, or Weights & Biases.
- Ability to move comfortably between executive conversations and deep technical discussions.
- Demonstrated experience working across multiple business domains and with cross-functional technical and business teams.
At BrainRidge Consulting, we value and prioritize diversity, equity, and inclusion. We believe that a diverse and inclusive workplace leads to a more innovative and productive team. We welcome applicants of all backgrounds and are committed to providing a safe, fair, and welcoming environment where everyone feels valued and respected. If you require accommodations during the hiring process, please let us know.
More about this job
Responsibilities
Design end-to-end enterprise AI architectures, platforms, and agentic systems, including retrieval, security, governance, evaluation, and production operations. Lead architecture workshops and proofs of concept, develop reusable standards and reference architectures, and provide technical leadership across business and engineering teams.
Requirements
Requires 7+ years of software or solutions architecture experience, including meaningful experience architecting AI or machine learning systems, and strong expertise in generative and agentic AI. Candidates should have cloud, data, enterprise architecture, and security experience, hands-on skills with Python, SQL, APIs, CI/CD, Docker, Kubernetes, and Infrastructure as Code, and the ability to work across technical and business teams.
Skills
- Generative AI
- Agentic AI
- Large Language Models
- Retrieval-Augmented Generation
- AI Architecture
- Cloud Architecture
- Python
- SQL
- Kubernetes
- Docker
- Infrastructure as Code
- Machine Learning
- Data Architecture
- MLOps/LLMOps/AgentOps
- Enterprise Security
- Distributed Systems
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Consulting
- Security & Safety
Keywords
- Generative AI
- Agentic AI
- Large Language Models
- Retrieval-Augmented Generation
- Machine Learning
- Multi-Agent Systems
- Tool Calling
- Context Engineering
- AI Memory
- Model Routing
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- AutoGen
- CrewAI
- Model Context Protocol
- OpenAI
- Anthropic Claude
- Google Gemini
- Azure
- AWS
- Google Cloud
- Vector Databases
- Hybrid Search
- Knowledge Graphs
- Python
- SQL
- Kubernetes
- MLOps