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PYTHON DEVELOPER - GENAI / LLM

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Summary

A senior (8-10 years) Python developer role placed at Citi Bank in Mississauga, building and deploying Generative AI/LLM applications. Day-to-day work centers on RAG pipelines, LLM app development and prompt engineering using Python, FastAPI, LangChain, PyTorch, vector databases, plus MLOps and Kubernetes/OpenShift deployment.

NOW HIRING: PYTHON DEVELOPER GENAI / LLM

Client: Citi Bank

Location: Mississauga, Ontario

Position: Python Developer

Employment: Full-Time

Experience: 8 10 Years

Salary: CAD $110K

Core Ai/Ml & Genai Skills

  • Generative AI / Machine Learning / Data Science
  • AI Fundamentals, NLP, Neural Networks & LLMs
  • Google Gemini / OpenAI / Anthropic Claude / Mistral / Llama
  • RAG Pipelines & Advanced RAG Techniques MUST HAVE
  • LLM Application Development, Tuning & Deployment
  • Vertex AI / Hugging Face
  • Prompt Engineering / Prompt Tuning / Reusable Prompt Templates
  • Agentic AI Frameworks
  • Guardrails, GenAI Evaluation & Safety

PYTHON & DATA ENGINEERING

  • Strong Python development
  • Pandas / NumPy / Scikit-learn
  • PyTorch / TensorFlow / Transformers
  • FastAPI / LangChain / LlamaIndex
  • GenAI Integration with Enterprise Applications
  • APIs / Knowledge Graphs / Orchestration Tools
  • Vector Databases PGVector / Pinecone / MongoDB Atlas / Neo4j

Large-Scale Unstructured Data & High-Throughput Processing

DEPLOYMENT & MLOPS

  • Production Deployment of GenAI Models MUST HAVE
  • MLOps / Model Evaluation
  • CI/CD Jenkins / GitLab CI / Azure DevOps / ArgoCD
  • Automated Build, Testing & Deployment Pipelines

CLOUD & CONTAINERIZATION

  • Kubernetes / OpenShift
  • Cloud-Native Application Deployment
  • Containerization, Scaling & Orchestration

IDEAL CANDIDATE

  • Strong problem-solving and analytical skills
  • Excellent communication and collaboration skills
  • Ability to work independently on complex and ambiguous problems
  • Strong experience working with cross-functional technical and business teams

Skills

See also

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