Senior Full-Stack AI Engineer

Who We Are

Welcome to TELUS Digital — where innovation drives impact at a global scale. As an award-winning digital product consultancy and the digital division of TELUS , one of Canada’s largest telecommunications providers, we design and deliver transformative customer experiences through cutting-edge technology, agile thinking, and a people-first culture.

With a global team across North America, South America, Central America, Europe, Africa, and APAC, we offer end-to-end expertise across various service offerings: Web, Mobile & Digital Marketing | Enterprise AI | Customer Care AI & Technology | Enterprise Technology Modernization

From mobile apps and websites to voice UI, chatbots, AI, customer service, and in-store solutions, TELUS Digital enables seamless, trusted, and digitally powered experiences that meet customers wherever they are — all backed by the secure infrastructure and scale of our multi-billion-dollar parent company.

Location & Flexibility

Our Senior Full-Stack AI Engineers are integral parts of our team at TELUS Digital. To help retain our deep culture of collaboration, this role will maintain an in-office presence in a hybrid capacity in Sofia, Bulgaria

The Opportunity

Business-level English proficiency (written and verbal) is required

As a Senior Full-Stack AI Engineer to help build and evolve the AI systems that power a leading gaming client's player support platform. This role sits at the center of two connected products: an AI assistant used directly by players, and an AI copilot used by the support agents who help them.

You'll work across the full stack — from LLM orchestration and agentic workflow design on the backend to the React applications and admin tooling that let the team configure, monitor, and improve these systems in production.

This is a hands-on engineering role for someone who has already shipped and operated production AI systems, not just prototyped them.

You'll design conversation flows that handle ambiguous intent, tool use, retrieval, and escalation to a human; evaluate and tune models across multiple providers; and build the observability and resilience that keep these systems reliable at scale.

Day-to-day, you'll work primarily in TypeScript across a Node.js backend and React frontend, using state machines to model complex conversational workflows and integrating with large language model providers such as OpenAI, Anthropic, and Gemini.

Responsibilities

AI Platform & Agent Systems

Design and extend production-grade LLM applications and agentic workflows, including RAG, intent detection, clarification, fulfillment, escalation, and human-in-the-loop flows

Build and maintain the underlying conversation engine, including flow validation, configuration tooling, and the admin experience used to manage it

Integrate tool-use and agentic protocols to extend what the AI assistant and copilot can do

Evaluate, benchmark, and tune models across multiple providers, owning model selection decisions that balance quality, latency, throughput, reliability, and cost

Troubleshoot production AI issues such as hallucinations, retrieval failures, prompt regressions, model drift, and provider outages

Build resilience mechanisms including retries, fallback routing, caching, streaming, and rate limiting

Instrument and tune model quality using tracing, evaluation datasets, A/B testing, and prompt versioning

Frontend & Admin Tooling

Build player-facing and support-agent-facing experiences in React

Develop and maintain the admin interface used to manage flows, intents, releases, translations, prompts, and evaluations

Integrate real-time, event-driven product features

Own frontend performance, accessibility, and internationalization

Platform & Quality

Write comprehensive automated tests across unit, integration, contract, and end-to-end layers

Build observability for both traditional services and AI systems, including tracing, dashboards, and alerting

Diagnose performance bottlenecks across application code, retrieval systems, model inference, and infrastructure

Participate in an on-call rotation and respond to production incidents with clear communication

Document architectural decisions and keep runbooks current

Qualifications

Proven experience building and operating production LLM-powered systems — chatbots, AI assistants, agent copilots, RAG systems, or LLM orchestration platforms

Strong TypeScript/Node.js engineering skills, with fluency in strict-mode TypeScript

Hands-on production AI experience: prompt engineering, RAG pipelines, agent design, tool calling, model evaluation, observability, and failure-mode analysis

Full-stack depth — comfortable moving between backend APIs, React UIs, databases, infrastructure, and production operations

Ability to evaluate tradeoffs between model quality, latency, reliability, throughput, and cost

Ability to troubleshoot AI systems across prompts, retrieval pipelines, model configuration, infrastructure, and application code

Experience modeling complex asynchronous workflows (state machine experience is a strong signal)

Solid understanding of REST API design, asynchronous patterns, and caching strategies

A strong testing culture, with unit, integration, and contract tests treated as first-class deliverables

Experience working in a monorepo with multiple interconnected services

Bonus Points

Experience with agentic tool-use protocols (e.g., MCP), semantic search/retrieval architectures, or AI gateways

Familiarity with LLM observability and evaluation platforms, and experience evaluating multiple foundation models or providers at scale

Experience building AI copilots, assistants, or other conversational products, especially under low-latency or streaming constraints

Hands-on experience with NestJS specifically

Background in customer support or player support platforms, gaming, or high-volume consumer products

Equal Opportunity Employer

At TELUS Digital, we are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. All aspects of employment, including the decision to hire and promote, are based on applicants’ qualifications, merits, competence and performance without regard to any characteristic related to diversity.

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