Forward Deployed Technical Consultant in Mississauga

We are: The Advanced Technology Centers (ATCs) are the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000 people across 24 countries, ATCs provide our clients with seamless access to industry insights and innovative technology solutions. Stronger together! The Advanced Technology Centers (ATCs) make a tremendous impact in solving our clients’ business problems by leveraging innovation, intelligence, industry insights, new IT, and new technology skills. With the global environment changing at a faster pace, our clients are facing unprecedented challenges, and they need us more than ever before. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients.

You Are: As a Forward Deployed Technical Consultant, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. You will design, build, and operationalize enterprise-grade data and agentic AI solutions on the Snowflake AI Data Cloud. Your role spans the full solution lifecycle of Snowflake-native data products and agentic AI systems — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. You’ll work closely with analytics, data science, and cloud teams to ensure reliable, high-performance data delivery for the clients we serve.

THE WORK

• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions.
• Architect and maintain a scalable, governed Snowflake AI Data Cloud environment including compute optimization, warehouse sizing, and cost management.
• Design and implement ELT/ETL frameworks using Snowflake SQL, Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe for batch, streaming, CDC, and event-driven ingestion patterns.
• Build reusable, AI-ready data products with clear ownership, semantic context, data quality SLAs, and lineage tracking.
• Design and build multi-step agentic AI workflows using Snowflake Cortex Agents, Cortex AI Functions, Cortex Search, and Cortex Analyst.
• Develop production-grade Retrieval-Augmented Generation (RAG) pipelines with vector search, semantic retrieval, and hybrid search capabilities over governed Snowflake datasets.
• Integrate AI agents with enterprise systems via MCP (Model Context Protocol) connectors, REST APIs, and event-driven messaging architectures.
• Implement tool-use orchestration, prompt engineering, and evaluation frameworks (LLMOps) for reliable, auditable AI agent behaviour.
• Apply agentic automation to operational use cases including anomaly detection, data quality remediation, query diagnosis, documentation generation, and incident summarisation.
• Build and maintain semantic data models that expose governed, business-ready datasets to Cortex Analyst and BI tools.
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites.
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production.
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
• Justify the value of model approaches in business problems.
• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production.

This is a hybrid role in Mississauga/Montreal and requires 3 days per week in the office/client location.

BASIC (REQUIRED) QUALIFICATION

• Bachelor’s degree or completion of a college program in Computer Science, or related field.
• 3+ years experience in Snowflake-native features: Snowpark (Python), Dynamic Tables, Streams & Tasks, Snowpipe, Cortex AI suite, and performance tuning.
• 3+ years experience in Python (data pipelining and ML workloads) and advanced SQL.
• Experience with data modelling methodologies and dbt for transformation layer management.
• Familiarity with at least one major cloud platform (AWS, Azure, or GCP) and associated services (object storage, IAM, networking, managed compute).
• Minimum of 3 years of experience in applying theoretical foundations of computer science, including computer system architecture, and programming.
• Minimum of 1 year of experience in distributed computing systems and architecture that may include big data, high-performance compute, scientific compute, grid and cloud computing, distributed networks.
• Minimum of 1 year of experience in building and deploying AI/ML based software to a cloud environment.
• English is required for this position as this role will regularly interact with stakeholders across Canada, US and other countries across our Global footprint where English is the common language.

PREFERRED QUALIFICATION

• Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).
• Experience with vector databases (e.g., Snowflake Vector Search, Pinecone, Weaviate) and embedding models (e.g., Snowflake Arctic Embed).
• Snowflake SnowPro Advanced certification (Data Engineer or Architect) or Cortex AI practitioner credentials.
• Hands-on experience with MLOps tooling: model registries, evaluation pipelines, experiment tracking, and monitoring in production.
• Familiarity with MCP (Model Context Protocol) and enterprise agentic control plane architectures.
• Exposure to streaming technologies (Apache Kafka, Kinesis) integrated with Snowflake ingestion pipelines.
• Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders.
• Strong client-facing skillsets in a consulting environment.