Cloud & AI Developer II

Summary

We are seeking a highly motivated and experienced Cloud & AI Developer to join Bell’s Finance AI Team within the Finance Business Unit. In this role, you will be embedded within the Finance organization as a hands-on developer, designing and deploying cloud-native applications on Google Cloud Platform (GCP) and building AI-powered solutions that serve Finance members across Bell.

You will build robust, low-latency cloud-native applications on GCP (Cloud Run, BigQuery, Vertex AI, Pub/Sub, GCS) and integrate them with production Finance systems — then layer in AI and LLM-powered capabilities to automate workflows, surface insights, and deliver intelligent tools that Finance teams rely on every day.

This is a high-impact, highly visible role for someone who thrives on building real things — shipping cloud applications and AI products that Finance stakeholders depend on, not just experimenting.

Key Responsibilities

• Build and maintain robust, low-latency cloud-native applications on GCP (Cloud Run, BigQuery, Vertex AI, Pub/Sub, GCS) for seamless integration with production Finance systems.
• Design, develop, and deploy AI-powered applications and LLM-based solutions (e.g., summarization pipelines, RAG systems, agentic workflows) tailored to Finance business use cases.
• Develop and fine-tune advanced predictive models and deep learning architectures to optimize key business and Finance-specific metrics.
• Leverage and integrate large language models (LLMs) via APIs (e.g., Gemini) and fine-tuning workflows to build intelligent Finance tools.
• Develop and maintain data pipelines using Python, SQL, Alteryx and Teradata for large structured and unstructured Finance datasets.
• Collaborate with Finance stakeholders to understand requirements, prototype solutions, and iterate quickly based on feedback.
• Effectively communicate data-driven insights and AI solution designs to both technical and non-technical Finance audiences.
• Champion cloud-first and AI-first development practices within the Finance AI team.
• Provide technical mentorship and actively contribute to a collaborative, innovative team environment.
• Proactively identify opportunities to apply new AI tools and methodologies to improve Finance processes and decision-making.
• Educate and promote AI adoption across the wider Finance organization — running demos, lunch-and-learns, and knowledge-sharing sessions to build AI literacy and excitement among Finance teams.

Critical Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, Applied Math, or a related field.
• 3+ years of relevant experience in AI/ML development, data science, or a software engineering role with strong ML exposure.
• Hands-on experience with Google Cloud Platform (GCP) — Cloud Run, BigQuery, Vertex AI, Pub/Sub, GCS, and Artifact Registry strongly preferred.
• Experience containerizing and deploying applications with Docker and CI/CD pipelines (e.g., GitLab CI/CD).
• Demonstrated experience building with large language models (LLMs) — including prompt engineering, RAG pipelines, LLM API integration and/or fine-tuning.
• Experience designing and deploying agentic AI workflows (e.g., tool-use, multi-step reasoning agents).
• Proficiency with ML/DL frameworks: scikit-learn, TensorFlow, Keras, or PyTorch.
• Advanced proficiency in Python — ability to write clean, efficient, production-ready code.
• Advanced proficiency in SQL; experience with Teradata in an enterprise data environment.
• Proficiency with VS Code and standard developer tooling (Git, notebooks, CLI environments).
• Familiarity with Alteryx for data preparation and analytic workflow automation is an asset.
• Strong analytical, problem-solving, and communication skills — able to explain AI solutions to Finance stakeholders.
• Proven ability to manage multiple projects simultaneously and deliver against deadlines.

Preferred Qualifications

• GCP Professional certifications.
• Experience building GenAI or LLM-powered applications in a production finance or enterprise environment.
• Knowledge of financial data concepts, reporting systems, or working within a Finance business unit.
• Experience with Vertex AI, Gemini APIs, or Google's Generative AI stack.