Senior Architect

Mphasis; Toronto; Hybrid; CAD 140,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Mphasis in Toronto is seeking an AI Architect to lead the design, architecture, and implementation of enterprise-scale Generative AI on Google Cloud Platform. You will drive RAG-driven knowledge platforms, LLM integrations, and scalable AI solutions across business units.

The role requires deep expertise in Vertex AI, Gemini, and related AI ecosystems, with hands-on engineering and strategic leadership in a hybrid environment.

Qualifications

• Bachelor’s degree or higher in computer science, data science, or related field.
• Deep knowledge of Generative AI and LLMs, including Gemini, Vertex AI, OpenAI, Llama, and foundation models.
• Experience with RAG, knowledge graphs, embeddings, and semantic search.
• Proficiency with GCP services: Vertex AI, BigQuery, Cloud Storage, Run, Functions, SQL, Pub/Sub, Dataflow, GKE.
• Familiarity with vector databases and search platforms such as Vertex AI Vector Search, Pinecone, ChromaDB, FAISS, pgVector.
• Experience with MLOps, CI/CD for AI, model governance, Terraform, and security governance.
• Certifications in Google Cloud AI/ML or Generative AI are a plus.

Responsibilities

• Define enterprise AI architecture standards, patterns, and best practices.
• Design end-to-end Generative AI, RAG, and Agentic AI solutions.
• Develop AI roadmaps aligned with business objectives and technology strategy.
• Architect large-scale RAG and GraphRAG solutions for enterprise knowledge bases.
• Design document ingestion, chunking, indexing, retrieval, grounding, and re-ranking strategies.
• Build scalable AI platforms with GCP services, focusing on performance, reliability, and cost.
• Lead the design and implementation of AI assistants, chatbots, copilots, and autonomous agents.
• Integrate LLMs with enterprise systems, APIs, and workflows.
• Establish frameworks for prompt engineering, model evaluation, and continuous improvement.
• Architect scalable AI platforms using GCP services and cloud-native deployment.
• Drive cloud-native AI application development and deployment, with governance and observability.
• Implement AI governance frameworks, security controls, and monitoring for compliance.
• Partner with stakeholders, lead design reviews, mentor teams, and promote AI adoption.

Skills

LLMs & Generative AI

GCP Vertex AI

RAG & Knowledge Graphs

Python

LangChain

Security & Governance

Multi-Agent Architectures

Education

Bachelor’s degree in Computer Science or related field

Tools

Vertex AI

BigQuery

Pinecone

ChromaDB

FAISS

Job description

Job Summary – AI Architect

We are seeking a highly experienced

Job Description

Job Summary – AI Architect

We are seeking a highly experienced AI Architect to lead the design, architecture, and implementation of enterprise-scale Generative AI solutions on Google Cloud Platform (GCP). The ideal candidate will possess deep expertise in Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Agentic AI, Vector Databases, and the Google AI ecosystem including Vertex AI and Gemini. The role requires a blend of strategic architecture leadership and hands-on technical expertise to deliver scalable, secure, and production-ready AI platforms.

Years of Experience:

• 10+ years of overall experience in software engineering, cloud architecture, or data platforms.
• 5+ years of experience designing and implementing AI/ML solutions.
• 3+ years of experience delivering Generative AI and LLM-based applications in enterprise environments.
• Proven experience implementing RAG architectures, conversational AI platforms, and AI-powered knowledge management solutions.

Required

Technical Skills:

• Bachelor’s degree in Computer Science, Data Science.
• Generative AI & LLMs: Gemini, Vertex AI, OpenAI, Llama, Foundation Models, Prompt Engineering, Conversational AI, Agentic AI / Multi-Agent Architectures, AI Model Evaluation and Monitoring
• RAG & Knowledge Systems: Retrieval-Augmented Generation (RAG), GraphRAG, Knowledge Graphs, Semantic Search, Embeddings and Vector Search, Document Intelligence and Enterprise Search
• Google Cloud Platform (GCP): Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Cloud SQL, Pub/Sub, Dataflow, GKE (Google Kubernetes Engine)
• Vector Databases & Search: Vertex AI Vector Search, Pinecone, ChromaDB, FAISS, pgVector
• AI Frameworks & Development: LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, Python, SQL
• MLOps & DevOps: Vertex AI Pipelines, MLflow, CI/CD for AI Applications, Model Governance & Monitoring, Infrastructure as Code (Terraform)
• Security & Governance: Responsible AI, AI Risk Management, Data Governance, Security Architecture, Compliance & Audit Controls

Preferred Certifications

• Google Cloud Professional Cloud Architect
• Google Cloud Professional Machine Learning Engineer
• Google Generative AI Certifications
• Databricks Generative AI Certifications (preferred)

Key Responsibilities

AI Architecture & Strategy

• Define enterprise AI architecture standards, patterns, and best practices.
• Design end-to-end Generative AI, RAG, and Agentic AI solutions.
• Develop AI roadmaps aligned with business objectives and technology strategy.

RAG & Knowledge Platform Design

• Architect large-scale RAG and GraphRAG solutions.
• Design document ingestion, chunking, indexing, retrieval, re-ranking, and grounding strategies.
• Optimize AI solution accuracy, scalability, latency, and cost efficiency.
• Build enterprise knowledge platforms leveraging structured and unstructured data sources.

Generative AI Solution Delivery

• Lead the design and implementation of AI assistants, chatbots, copilots, and autonomous agents.
• Enable integration of LLMs with enterprise systems, APIs, and workflows.
• Establish frameworks for prompt engineering, model evaluation, and continuous improvement.

Cloud & Platform Engineering

• Architect scalable AI platforms using GCP services.
• Drive cloud-native AI application development and deployment.
• Define best practices for performance optimization, reliability, observability, and resilience.

Governance, Security & Responsible AI

• Implement AI governance frameworks, security controls, and monitoring capabilities.
• Ensure compliance with enterprise policies, data privacy, and regulatory requirements.
• Establish standards for model transparency, explainability, and risk management.

Leadership & Collaboration

• Partner with business stakeholders, product owners, data engineers, and AI teams.
• Conduct architecture reviews and technical design workshops.
• Mentor engineering teams and promote AI adoption across the organization.
• Present architecture recommendations and investment strategies to executive leadership.

Location:

Toronto, ON

Work Mode:

Hybrid, 3-4 days per week

About Mphasis

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.

Equal Opportunity Employer

Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders. View the EEO in the law poster , view the EEO in the law supplement . To view the pay transparency nondiscrimination provision please click and to view the E-Verify posting click .

Mphasis is committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of disability to search and apply for a career opportunity, please send an email to [e-mail] and let us know your contact information and the nature of your request.