Senior Architect

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.

Technical Skills:

Required:

• Bachelors 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 (CX2C2TM1) 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 .

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