solutions architect - information technology (IT)

Req Id: 432449Connection is everything. It drives us to innovate, explore, and stay close to what matters to us most. At Bell, we're building a more connected future through world-class networks, AI-powered solutions, and digital experiences that elevate how people live, work, and play every day. We believe in empowering people.

That's why we equip our teams with cutting-edge technology, AI tools, and a collaborative environment that supports creativity and growth. Want to be part of a diverse team where your work makes a real impact? If you're inspired by innovation that advances how people connect and transforms what's possible, you belong on #TeamBell.

SummaryBell is seeking a Conversational AI Developer to join an innovative, customer-focused team. You'll build and improve virtual assistants that help Bell customers get answers and get things done, using Google's CX Agent Studio and Dialogflow CX. This is a hands-on role for a curious, resourceful problem solver who wants to grow their skills in conversational AI, LLM-powered experiences, and AI agents.

Working within an Agile framework, you'll collaborate with senior developers, architects, conversational designers, and product owners to deliver solutions that evolve with our customers' needs. Key

Responsibilities

Build, configure, and maintain conversational AI assistants using CX Agent Studio, and learn and contribute to Dialogflow CX flows, intents, pages, and webhooks. Implement conversation flows and dialogue logic based on designs from conversational designers and architects. Develop integrations with backend services and APIs using JSON and other data interchange formats.

Write, test, and refine prompts and agent instructions, and help manage the context (conversation history, retrieved knowledge, and tool outputs) that agents use to respond accurately. Implement and troubleshoot tool calling, connecting agents to APIs, data sources, and backend systems so they can complete tasks for customers.

Support the implementation of LLM-based and agentic features, including knowledge retrieval and multi-step agent behaviours, under the guidance of senior team members. Explore and prototype with emerging agent frameworks and protocols (e.g., ADK, MCP, A2A) as the team evaluates them.

Test and troubleshoot assistants, including end-to-end conversational flow testing, to identify and resolve defects and improve accuracy. Review performance data and customer interactions to find opportunities for continuous improvement, and help tune intents, prompts, and fallback handling.

Contribute to multi-channel deployments (web, mobile, messaging, IVR) while following enterprise security, privacy, and governance standards. Document your work, participate in Agile ceremonies (stand-ups, sprint planning, retros, PI Planning), and track tasks in JIRA. Stay current on evolving conversational AI and LLM trends and share what you learn with the team. Critical

Qualifications

Strong problem-solving skills and a logical, analytical approach to debugging and improving systems. Foundational understanding of Natural Language Understanding (NLU) and Large Language Models. Working knowledge of prompt engineering: writing clear instructions, using examples, and iterating on prompts based on results.

Basic understanding of context engineering: how conversation history, retrieved information, and tool results shape LLM behaviour and quality. Basic understanding of tool/function calling and how LLM agents interact with external APIs and systems.

Experience with, or strong interest in learning, conversational AI platforms such as CX Agent Studio and Dialogflow CX (through work, academic projects, internships, or personal projects). Working knowledge of JSON and REST APIs. Programming experience in at least one language (e.g., Python, JavaScript/Node.js). Basic familiarity with cloud platforms (GCP preferred, Azure or AWS also relevant).

Good written and verbal communication skills, with the ability to explain