AI Development Consultant

Job summary

Design, develop, maintain, and deploy scalable AI applications and full-stack solutions, integrating data from APIs, relational databases, and vector databases. Support business initiatives by improving AI platforms and data science systems, developing predictive or statistical models, and ensuring product quality across environments.

Job details

Dawn InfoTek Inc. is a professional IT consulting firm that partners with major financial institutions, investment firms, and government organizations. We are committed to delivering cutting-edge IT consulting services and providing highly qualified talent for a wide range of technology positions. We are currently seeking a AI Development Consultant to join our dynamic team and work with one of our major clients Contract Duration: ASAP to December 24, 2027 Role type: Hybrid (2 days per week in office - Downtown Toronto) Overview As an AI Development Consultant, you will be responsible for designing, implementing, and maintaining AI applications. You will work closely with AI engineers, data scientists, and business stakeholders to understand requirements and deliver scalable solutions. Who you'll work with: You’ll join the Applied Intelligence team, which is a multidisciplinary group of data scientists, data analytics specialists, software engineers and UX experts. In this team, you will work in a highly collaborative environment to deliver high-quality AI solutions. You’ll also work directly with our internal business team clients (Capital Markets, Private Investment, and more). What you'll do: The Applied Intelligence team is mandated to build AI capabilities for the organization and enable an AI augmented workforce. Support business initiatives in developing, maintaining and improving AI platforms. Design and develop efficient, scalable, and reliable software used by the whole organization. Integrate data from different sources, including APIs, relational databases and vector databases. Full-stack solutions development – web front-end, back-end APIs, and databases Responsible for ensuring product quality and deployment to different environments Opportunity to work with different AI models, assist and develop predictive analysis, and/or statistical modelling Be able to research independently for potential solutions to problems encountered in programming Maintain, monitor, and improve data science ecosystem: data pipeline, statistical model development and/or business applications What you'll need: Bachelor’s or Master’s degree in quantitative domains: Mathematics, Statistics, Computer Science, or Engineering. 2+ years’ experience in business-oriented analytics or software engineering. Passion for problem solving to support investment decision making Self-motivated, ability to do independent research Strong communication skills, ability to articulate thoughts / ideas to effectively collaborate with a variety of teams from both investments and technology Strong desire to work in a team-based and collaborative environment Strong programming skills (e.g. Python, SQL) Experience in developing with LLMs is a must. Must have hands on experience in building AI Agents, RAG models, and working with ML models. Full-stack programming experience with React/Angular, Python Flask Experience with automated testing Familiarity with CICD (Continuous Integration and Continuous Deployment) practices for data engineering projects Knowledge of cloud platforms (e.g., Azure, AWS, GCP) and related services Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)

What you’ll do

Design, develop, maintain, and deploy scalable AI applications and full-stack solutions, integrating data from APIs, relational databases, and vector databases. Support business initiatives by improving AI platforms and data science systems, developing predictive or statistical models, and ensuring product quality across environments.

Requirements

A bachelor’s or master’s degree in a quantitative field and at least two years of experience in business-oriented analytics or software engineering are required. Candidates need strong Python and SQL skills, hands-on experience with LLMs, AI agents, RAG, and machine learning models, plus full-stack development experience and familiarity with testing, CI/CD, cloud platforms, and containerization.

Listed skills

• Kubernetes · Preferred
• SQL · Preferred
• Automated testing · Preferred
• Angular · Preferred
• Docker · Preferred
• React · Preferred
• Machine learning · Preferred
• Python · Preferred
• Flask · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• Large Language Models
• AI Agents
• Retrieval-Augmented Generation
• Machine Learning
• React
• Angular
• Flask
• Automated Testing
• Continuous Integration and Continuous Deployment
• Cloud Platforms
• Docker
• Kubernetes
• Data Pipelines
• Statistical Modeling

Job areas

• Technology
• Software
• Data & Analytics
• Consulting
• Finance & Accounting