Job Specifications
Job Title
GenAI Architect
Location-Toronto- Canada / Hybrid
Experience
10+ years overall IT experience, with 3–5+ years in AI/ML and Generative AI architectures
Role Summary
We are seeking an experienced Generative AI (GenAI) Architect to design, govern, and scale enterprise-grade GenAI solutions. The ideal candidate will be responsible for defining GenAI architecture patterns, selecting appropriate models and platforms, ensuring security and compliance, and enabling business teams to derive measurable value from Generative AI use cases.
This role requires deep expertise across LLMs, cloud platforms, AI frameworks, MLOps, and responsible AI practices, with the ability to translate business problems into robust, production-ready GenAI architectures.
Key Responsibilities
GenAI Architecture & Design
Define end-to-end GenAI solution architectures, including model selection, orchestration, data pipelines, and integration layers.
Design scalable patterns for RAG (Retrieval Augmented Generation), agents, fine-tuning, and prompt engineering.
Establish reference architectures, reusable components, and best practices for GenAI adoption.
Platform & Model Strategy
Evaluate and select LLMs and GenAI platforms (open-source and commercial) based on cost, performance, security, and regulatory needs.
Define hybrid architectures leveraging cloud-hosted and on-prem GenAI models where required.
Guide decisions on fine-tuning vs prompt-based approaches.
Engineering & Integration
Work closely with engineering teams to integrate GenAI solutions into enterprise systems (APIs, microservices, workflows).
Ensure robust integration with data platforms, vector databases, and enterprise applications.
Provide architectural oversight during development and deployment.
MLOps, Security & Governance
Define MLOps / LLMOps standards for model versioning, monitoring, observability, and lifecycle management.
Ensure compliance with data privacy, security, and Responsible AI principles.
Collaborate with legal, security, and compliance teams on AI governance frameworks.
Stakeholder Engagement
Partner with business leaders, product teams, and clients to identify high-value GenAI use cases.
Act as a trusted advisor, translating technical capabilities into business outcomes.
Mentor teams on GenAI concepts, tools, and architectural thinking.
Key Technologies & Frameworks
Large Language Models (LLMs)
OpenAI / Azure OpenAI (GPT-4.x)
Anthropic Claude
Open-source LLMs (LLaMA, Mistral)
GenAI Frameworks
LangChain
LlamaIndex
Semantic Kernel
Vector Databases & Retrieval
Azure AI Search
Pinecone / FAISS
Cloud & AI Platforms
Microsoft Azure (Azure AI, Azure OpenAI)
Kubernetes (for scalable AI workloads)
Programming & Integration
Python
REST APIs / Microservices
MLOps & Governance
MLflow (or equivalent)
Responsible AI, data privacy, and security frameworks
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
10+ years of experience in solution or enterprise architecture.
Hands-on experience designing and deploying Generative AI solutions in production.
Strong understanding of cloud architecture, data platforms, and AI lifecycle management.
Proven ability to communicate complex technical concepts to senior stakeholders.
About the Company
We are a dedicated Salesforce CREST partner committed to empowering businesses by effectively leveraging Salesforce solutions. Businesses lack technical expertise to be able to implement, maintain, and optimize the Salesforce platform. We, at Simpliigence, help by breaking down business challenges into technical solutions, and help businesses not only implement, but also manage the Salesforce platform, swiftly and in cost-effective way.
We make it easier for the businesses to leverage the most innovating SaaS platform i.e...
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