Senior Full-Stack Data & AI Engineer

Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.

Don't just work, thrive. At Bridgenext, you have an opportunity to make a real difference - driving tangible business value for clients, while simultaneously propelling your own career growth. Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed. 

Bridgenext is seeking a Senior Full-Stack Data & AI Engineer to own the complete data lifecycle—from ingestion and engineering through data modeling, analytics, AI enablement, and front-end consumption—within a cloud-native Azure ecosystem.

The role requires strong hands-on expertise in Python-based data engineering, analytics, and AI integration using FastAPI, along with the ability to build or support dashboards and data-driven front-end applications that deliver business-ready outputs.

The Senior Engineer will be responsible for owning the full data product lifecycle—requirements, build, deploy, run, and optimize—delivering reusable, governed, high-quality data assets and integrating RESTful APIs with enterprise platforms. Solutions are expected to run on Azure Kubernetes Service (AKS) with built-in authentication, authorization, and scalability.

This role focuses on delivering robust, production-ready data products with a data product mindset—reusable, governed, and aligned to business outcomes—within an existing Azure-centric framework. It is positioned as a full-stack Data & AI Engineering role, not a traditional full-stack development position.

Responsibilities include but are not limited to:

• Design, develop, and own end-to-end data solutions spanning data ingestion, engineering, modeling, analytics, AI, and front-end consumption
• Build and maintain RESTful APIs using FastAPI with authentication, rate limiting, pagination, and error handling
• Develop scalable data pipelines and backend services using Python for data ingestion, transformation, and orchestration
• Build or support dashboards and data-driven applications (e.g., Power BI, React UI) to enable front-end consumption of data products and KPIs
• Design and implement conceptual, logical, and physical data models; build and maintain semantic layers to ensure consistent, governed data access
• Deploy and operate containerized data and AI applications on Azure Kubernetes Service (AKS)
• Enable ML/LLM use cases including chat, summarization, RAG, agents, and evaluators; prepare and manage data for model training and inference
• Integrate data pipelines and applications with Azure OpenAI and other AI services to power intelligent, data-driven features
• Deliver analysis-ready datasets, KPIs, and business-ready outputs aligned to stakeholder requirements; collaborate with cross-functional teams and participate in code reviews
• Own the full lifecycle of data products: requirements gathering, build, deployment, operational monitoring, and continuous optimization

Workplace: Hybrid in the Greater Toronto Area

Must Have Skills:

• 8+ years of professional experience in data engineering, analytics engineering, or full-stack data platform development
• Experience building or supporting dashboards and data-driven applications using tools such as Power BI, React, or similar frameworks
• Strong proficiency in Databricks
• Strong experience building RESTful APIs using FastAPI
• Expertise in SQL databases (PostgreSQL, MySQL, SQL Server) with strong data modeling skills (conceptual, logical, physical models and semantic layers)
• Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis for diverse data storage needs
• Hands-on experience deploying containerized data and AI applications on AKS
• Experience enabling ML/LLM use cases including data preparation for training/inference, RAG, chat, and summarization
• Experience integrating data pipelines with Azure OpenAI and other AI services
• Strong proficiency in Python programming with a data product mindset—building reusable, governed, high-quality data assets aligned to business outcomes

Preferred Skills:

• Good understanding of Agentic AI frameworks such as LangChain or AutoGen
• Exposure to Agent-to-Agent (A2A) communication and agent scaling
• Azure data platform experience including Data Factory, Synapse, Purview, Entra ID fundamentals, and app registrations
• Knowledge of OAuth2, OIDC, SSO, and SAML configurations; familiarity with data governance and cataloging tools

Professional Skills:

• Solid written, verbal, and presentation communication skills
• Strong team and individual player
• Maintains composure during all types of situations and is collaborative by nature
• High standards of professionalism, consistently producing high quality results
• Self-sufficient, independent requiring very little supervision or intervention
• Demonstrate flexibility and openness to bring creative solutions to address issues 

Bridgenext is an Equal Opportunity Employer

Canadian citizens and those authorized to work in Canada are encouraged to apply

Compensation varies depending on a wide array of factors, which may include but are not limited to location, role, skill set, and level of experience. As required by local law, Bridgenext provides a reasonable range of compensation, based on full-time employment, for roles that may be hired as described above. The current salary range for this position is $130,000 - $150,000 CAD annually. Our comprehensive total rewards program goes way beyond a competitive salary.

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