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Technology Lead - AI Lead Developer

Job in Mississauga, Ontario, Canada
Listing for: Infosys Limited
Full Time position
Listed on 2026-09-24
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 93000 - 123000 CAD Yearly CAD 93000.00 123000.00 YEAR
Job Description & How to Apply Below

PYTHON|Technology|Artificial Intelligence|Artificial Intelligence - ALL, Technology|data science

Domain

Delivery

Interest Group

Company

ITL Canada

Requisition

153526

Infosys is seeking a AI Lead Developer
. In this exciting role, you will lead the architecture, development, and production deployment of enterprise Generative AI solutions. You will combine hands-on Python engineering with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, and AI evaluation, while guiding development teams and collaborating with business, data, security, architecture, and platform stakeholders.

Required Qualifications
  • Candidate must be located within commuting distance of Toronto/Mississauga, Ontario or be willing to relocate to the area. This position may require travel.
  • Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
  • At least 4 years of Information Technology experience.
  • Candidates authorized to work for any employer in Canada without employer based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.

Infosys is seeking a AI Lead Developer
. In this exciting role, you will lead the architecture, development, and production deployment of enterprise Generative AI solutions. You will combine hands-on Python engineering with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, and AI evaluation, while guiding development teams and collaborating with business, data, security, architecture, and platform stakeholders.

Required Qualifications
  • Candidate must be located within commuting distance of Toronto/Mississauga, Ontario or be willing to relocate to the area. This position may require travel.
  • Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
  • At least 4 years of Information Technology experience.
  • Candidates authorized to work for any employer in Canada without employer based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
Preferred Qualification
  • A minimum of 8 years of software development experience, including strong hands-on Python development and delivery of enterprise-grade applications.
  • Strong theoretical and practical understanding of Generative AI concepts, including Large Language Models (LLMs), Small Language Models (SLMs), embeddings, context management, prompt engineering, structured outputs, and model selection.
  • Hands-on experience designing and implementing Agentic AI solutions, including tool use, function calling, planning, memory, orchestration, multi-agent workflows, confidence thresholds, exception handling, and human-in-the-loop controls.
  • Strong experience building Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embedding generation, vector indexing, semantic or hybrid retrieval, reranking, grounding, citation validation, and access-control alignment.
  • Experience creating evaluation frameworks for LLM, RAG, and agentic systems using golden datasets, offline benchmarks, regression tests, LLM-as-judge approaches where appropriate, and online quality metrics.
  • Knowledge of model quality and safety assessment, including relevance, groundedness, faithfulness, hallucination detection, retrieval quality, task completion, latency, cost, and reliability.
  • Knowledge of AI security and Responsible AI practices, including prompt-injection protection, data privacy, secure tool access, least-privilege…
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