AI Developer – Calgary

About the role

Infosys is seeking an AI Developer to join its Calgary team. The role focuses on building Retrieval‑Augmented Generation (RAG) pipelines, agentic orchestration, and advanced prompt engineering for contact‑center and conversational AI solutions.

Key responsibilities

• Design and implement custom RAG pipelines, including chunking, embeddings, hybrid search, re‑ranking and domain‑specific retrieval logic.
• Develop multi‑step agents with working memory, tool execution, state tracking and deterministic control flows.
• Optimize prompts, context packing and token economics to improve reasoning quality while reducing latency and cost.
• Build and maintain transparent AI micro‑services using FastAPI and standard HTTP clients.
• Create JSON schema definitions and Pydantic models for structured data extraction.
• Write unit tests, regression tests for RAG components and debug prompts.
• Instrument observability metrics such as tracing, logging and token/latency reporting.

Required profile

• Bachelor’s degree or equivalent, or three years of progressive experience in lieu of each year of education.
• Minimum 4 years of IT experience, with at least 2 years in contact‑center or conversational AI architecture.
• Authorized to work in Canada without employer‑based visa sponsorship.
• Willingness to relocate to or commute within Calgary.

Required skills

• Strong software engineering fundamentals in Python, including async programming and performance tuning.
• Hands‑on experience with FastAPI for building AI micro‑services.
• Knowledge of JSON schemas, Pydantic models and structured extraction techniques.
• Experience building RAG pipelines, embeddings, hybrid search and re‑ranking.
• Agentic programming skills: tool‑use flows, working memory, state machines.
• Prompt engineering and context optimization for large language models.
• Proficiency with HTTP clients, raw API calls and minimal‑framework AI development.
• Testing and debugging expertise, including unit tests and regression testing for AI components.
• Observability skills: tracing, logging, token and latency metrics.