Derex Technologies Inc specializes in providing IT consulting, staffing solutions and software services. Globally headquartered in Harrison New Jersey since 1996 Derex delivers the highest quality technology professionals and an array of customized IT talent solutions designed to improve productivity and drive results to global clients throughout North America.

With over two decades of unparalleled experience, Derex provides supports to its clientele, across such industries as Systems Integration, Banking and Finance, Telecommunications, Pharmaceutical and Life Sciences, Energy, Healthcare, Technology, Transportation, and local and federal Government agencies.

Job Description AI Architect

Please look for only who are located in

Canada .

About the job

We are seeking a visionary and highly experienced

AI Architect

to lead the design and delivery of next-generation intelligent solutions across our enterprise. This role is central to our digital transformation strategy and will focus on architecting robust, scalable, and secure AI-driven platforms and capabilities.

As an

AI Architect , you will bring deep

expertise in Artificial Intelligence, Machine Learning, Generative AI, Coding Assistants, AI Assistants, and Agile software engineering practices . You will guide the full AI lifecycle from conceptualization and solution design to model development, testing, and successful deployment into production environments. The ideal candidate will have a proven architectural background, hands-on experience with modern AI platforms, and a strong track record of delivering complex, enterprise‑grade intelligent systems. You will collaborate closely with cross-functional technology and business teams to shape the future of our AI ecosystem and accelerate innovation across the organization.

Must Have Skills:

Deep proficiency with

AI/ML frameworks and libraries

including

TensorFlow, PyTorch, and Keras , with the ability to architect scalable training and inference pipelines.

Advanced understanding of

Generative AI architectures , including

GANs, VAEs, transformer-based models , and experience applying these techniques to real-world enterprise use cases.

Practical experience using

AI Coding Assistants

Hands-on expertise with

Agentic AI platforms , including

Microsoft Copilot Agents, AutoGPT, CrewAI, Anthropic Claude , and other autonomous workflow systems.

Strong command of

Cloud & MLOps platforms , such as

AWS SageMaker, Azure Machine Learning, Google AI Platform , including experience building automated model deployment, monitoring, and retraining pipelines.

Solid experience architecting solutions on major cloud platforms ( AWS, Azure, GCP ), including familiarity with cloud-native AI, data,



and security services.

Proven ability to

mentor, guide, and provide architectural direction

to junior and mid-level AI/ML engineers across multiple projects.

Ability to conduct

AI/ML and Generative AI code reviews , ensuring adherence to architectural standards, performance benchmarks, and responsible AI practices.

Strong analytical and problem‑solving skills, including the ability to rapidly diagnose and resolve complex issues in

AI systems, ML pipelines, and application runtimes .

Excellent communication skills, capable of translating complex AI concepts for both

technical teams

and

business stakeholders .

Ability to define and implement

AI governance frameworks , including

Responsible AI guidelines, compliance controls, model guardrails, safety protocols , and risk‑mitigation practices.

Responsibilities:

Architect, design, and guide the implementation of

enterprise grade AI and ML solutions

that solve complex business problems and power intelligent applications.

Lead collaboration with

data scientists, ML engineers, platform engineers, and software teams

to integrate AI capabilities into products, platforms, and enterprise workflows.

Provide hands‑on technical leadership in

Python , including proficiency with

ML, GenAI, and LLM frameworks

(TensorFlow, PyTorch, HuggingFace, LangChain, etc.).

Oversee end-to-end

data preparation, feature engineering, vectorization, and model development , ensuring data quality and readiness for LLMs and Generative AI workloads.

Continuously evaluate emerging advancements in

AI, ML, LLMs, Agentic Systems , and incorporate relevant innovations into architectural roadmaps and solution designs.

Optimize AI and Generative AI models for

performance, latency, scalability, observability, and cost efficiency , leveraging cloud-native and distributed compute environments.

Conduct and drive

technical design reviews, code reviews, and architecture assessments

to ensure high standards of quality and engineering rigor.

Diagnose, troubleshoot, and resolve complex AI system issues to maintain the

reliability, accuracy, and security

of production AI applications.

Generative AI, Copilots & Coding Assistants

Design and architect enterprise-wide capabilities leveraging

AI coding assistants, copilots,



and developer productivity tools

(e.g., GitHub Copilot, Azure AI Studio assistants).

Lead the development of

extensions, plugins, and integrations

for IDEs like Visual Studio Code, IntelliJ IDEA, and Eclipse to embed AI‑driven developer workflows.

Apply deep understanding of

prompt engineering, LLM behaviour, context-window optimization, fine‑tuning, and agentic workflows

to enhance solution performance.

Design, train, and evaluate

custom generative models , exploring architectures such as

GANs, VAEs, diffusion models, and transformer-based architectures .

Architect pipelines for

data acquisition, cleaning, text chunking, retrieval augmentation (RAG) , and ingestion into vector stores.

Integrate enterprise solutions with

AI platforms and APIs

such as OpenAI, Azure OpenAI, LangChain, and other orchestration frameworks.

Design and maintain the

LLM data layer

using technologies like

Azure Cosmos DB, Azure AI Search , vector stores, and embedding indexes.

Develop

agentic automation

solutions using frameworks such as

LangChain, LlamaIndex, Semantic Kernel, and AutoGen , and integrate them with enterprise systems.

Apply robust DevOps practices using

CI/CD pipelines, GitHub Actions, Azure DevOps , and modern testing frameworks to maintain robust and automated AI development workflows.

Contribute to or lead copilot initiatives across domains such as

application development, customer support, operations, and productivity automation .

Prompt Engineering

Design, test, and refine

high-quality prompts , prompt templates, and generative AI interaction models tailored to organizational use cases.

Work closely with

product, content, and data teams

to align prompt behaviour with business outcomes, brand voice, and user experience requirements.

Continuously improve prompt structures to enhance

accuracy, relevance, safety, and contextual understanding

within AI/LLM systems.

Experiment with novel prompting strategies - chain-of-thought, retrieval-augmented prompts, tool-augmented prompts, system message optimization to improve AI performance.

Build and maintain an

enterprise prompt library , ensuring versioning, governance, reuse, and integration into automated workflows and applications.

Participate in fine‑tuning and reinforcement learning processes by designing

ground‑truth prompts, evaluation prompts, and tuning datasets .

Diagnose and refine prompts that yield suboptimal or incorrect results, ensuring predictable and aligned LLM behaviour across use cases.

Additional Information All your information will be kept confidential according to EEO guidelines.

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📌 AI Architect (Winnipeg)
🏢 Derex Technologies
📍 Winnipeg