Python Developer
Posted
Summary
Senior Python Developer in Mississauga building production GenAI/LLM applications: designing RAG pipelines and agentic workflows, engineering prompts, and deploying models via Vertex AI/Hugging Face on Kubernetes, using Python ML stack (PyTorch, TensorFlow, LangChain, FastAPI) and MLOps/CI-CD tooling.
We are looking for a Senior Python Developer with strong hands‑on experience in Generative AI, LLMs, RAG, and production AI solutions.
Required Skills
- 8–10 years of relevant experience in application development or systems analysis
- Strong foundation in AI/ML, Generative AI, Machine Learning, NLP, Neural Networks, Statistics, and LLMs
- Hands‑on experience with Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama, or similar LLMs
- Deep hands‑on experience with RAG pipelines and advanced RAG techniques
- Experience building and deploying LLM‑based applications using Vertex AI / Hugging Face
- Strong Prompt Engineering, Prompt Tuning, and reusable prompt templates
- Hands‑on experience with Agentic AI frameworks
- Experience with AI Guardrails, model evaluation, and GenAI safety
- Strong experience with Pandas, NumPy, scikit‑learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, and LlamaIndex
- Experience with Vector Databases such as Pinecone, PGVector, MongoDB Atlas, or Neo4j
- Hands‑on experience deploying GenAI/ML solutions to production
- Strong understanding of MLOps, CI/CD, model evaluation, and deployment pipelines
- Experience with Jenkins, GitLab CI, Azure DevOps, or ArgoCD
- Hands‑on experience with Kubernetes or OpenShift
What they ask for
Required
- 8-10 years of relevant experience in application development or systems analysis
- Strong foundation in AI/ML, Generative AI, Machine Learning, NLP, Neural Networks, Statistics, and LLMs
- Hands-on experience with Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama, or similar LLMs
- Deep hands-on experience with RAG pipelines and advanced RAG techniques
- Experience building and deploying LLM-based applications using Vertex AI / Hugging Face
- Strong Prompt Engineering, Prompt Tuning, and reusable prompt templates
- Hands-on experience with Agentic AI frameworks
- Experience with AI Guardrails, model evaluation, and GenAI safety
- Strong experience with Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, and LlamaIndex
- Experience with Vector Databases such as Pinecone, PGVector, MongoDB Atlas, or Neo4j
- Hands-on experience deploying GenAI/ML solutions to production
- Strong understanding of MLOps, CI/CD, model evaluation, and deployment pipelines
- Experience with Jenkins, GitLab CI, Azure DevOps, or ArgoCD
- Hands-on experience with Kubernetes or OpenShift
Skills
- Agentic AI
- AI
- Anthropic
- Argo CD
- Azure
- Azure DevOps
- CI/CD
- Claude
- DevOps
- FastAPI
- Gemini
- Generative AI
- GitLab
- Hugging Face
- Jenkins
- Kubernetes
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- Mistral
- MLOps
- Model Evaluation
- MongoDB
- Neo4j
- Neural Networks
- NLP
- NumPy
- OpenAI
- OpenShift
- pandas
- pgvector
- Pinecone
- Prompt Engineering
- Python
- PyTorch
- scikit-learn
- Statistics
- TensorFlow
- Transformers
- Vector Databases
- Vertex AI