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Python Developer - Genai​/Ai

Job in Mississauga, Ontario, Canada
Listing for: SIDRAM TECHNOLOGIES
Full Time position
Listed on 2026-09-23
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Python, Data Scientist
Salary/Wage Range or Industry Benchmark: 120000 - 180000 CAD Yearly CAD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: PYTHON DEVELOPER - GENAI / AI

NOW HIRING: PYTHON DEVELOPER GENAI / AI

Location:

Mississauga, Ontario, Canada

Client:
Citi Bank

Employment:
Full-Time

Overall

Experience:

10 Years

Relevant

Experience:

8 10 Years

Role Overview

Looking for a Python Developer with strong expertise in Generative AI, LLMs, RAG, Agentic AI, Data Engineering, and MLOps to build and deploy enterprise-grade AI solutions.

Core Ai/Ml & Genai Skills
  • GenAI, Machine Learning, Data Science, Statistics, NLP, Neural Networks, and LLMs.
  • Hands-on experience with Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama, and open-source LLMs.
  • Strong hands-on expertise with RAG pipelines and advanced RAG techniques.
  • Experience with Vertex AI, Hugging Face, and LLM application development.
  • Prompt engineering, prompt tuning, and reusable prompt templates.
  • Agentic AI frameworks and use-case implementation.
  • Guardrails and GenAI performance/safety evaluation.
PYTHON & DATA ENGINEERING
  • Strong Python programming.
  • Pandas, Num Py, Scikit-learn, PyTorch, Tensor Flow, Transformers.
  • FastAPI, Seaborn, Lang Chain, Llama Index.
  • GenAI integration with enterprise applications using APIs, knowledge graphs, and orchestration tools.
  • Vector databases: PGVector, Pinecone, MongoDB Atlas, Neo4j.
  • Experience handling large-scale unstructured data and high-throughput processing.
DEPLOYMENT & MLOPS
  • Production deployment of GenAI-based models.
  • MLOps, model evaluation, and deployment pipelines.
  • CI/CD:
    Jenkins, Git Lab CI, Azure Dev Ops, ArgoCD.
  • Kubernetes / Open Shift for cloud-native application deployment and scaling.
Soft Skills
  • Strong problem-solving and analytical skills.
  • Excellent collaboration and communication.
  • Ability to work independently on complex and ambiguous problems.
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