MW
Senior AI Developer/Lead (Python + LLM)
Mamsys World
Mississauga · Hybrid Full-time Lead 2w ago
About the role
Senior AI Developer/Lead (Python + LLM)
Location: Mississauga, Canada (Hybrid)
About the Role
We are hiring experienced AI Developers with strong expertise in Generative AI, Machine Learning, and Large Language Models (LLMs). This role involves building scalable, enterprise-grade AI solutions and working on cutting‑edge GenAI use cases within a high‑impact Scrum team.
Key Responsibilities
- Design, develop, and deploy LLM-powered applications
- Build and optimize RAG (Retrieval‑Augmented Generation) pipelines
- Implement advanced prompt engineering and reusable prompt templates
- Develop agent‑based AI solutions using modern frameworks
- Integrate AI solutions with enterprise systems using APIs and orchestration tools
- Work with vector databases for efficient data retrieval
- Handle large‑scale unstructured data processing
- Deploy models in production using MLOps and CI/CD pipelines
- Collaborate with cross‑functional teams in an Agile/Scrum environment
Required Skills & Experience
Core AI/ML Expertise
- Strong foundation in Machine Learning, Data Science, NLP, Neural Networks, and LLMs
- Hands‑on experience with leading LLMs (OpenAI, Gemini, Claude, Llama, Mistral, etc.)
- Deep expertise in RAG pipelines (mandatory)
Programming & Tools
- Strong proficiency in Python (mandatory)
- Experience with libraries: Pandas, NumPy, scikit‑learn, PyTorch, TensorFlow, Transformers
- Frameworks/Tools: FastAPI, LangChain, LlamaIndex, Hugging Face
Data & Integration
- Experience with vector databases (Pinecone, Mongo Atlas, Neo4j, PG Vector)
- Knowledge of APIs, knowledge graphs, and orchestration tools
Deployment & Cloud
- Strong experience in MLOps, model deployment, and CI/CD pipelines
- Tools: Jenkins, GitLab CI, Azure DevOps, ArgoCD
- Experience with Kubernetes/OpenShift and cloud platforms
Preferred Qualifications
- Experience with Vertex AI or similar platforms
- Knowledge of AI guardrails, evaluation frameworks, and safety mechanisms
- Exposure to agentic frameworks and advanced GenAI architectures
Requirements
- Strong foundation in Machine Learning, Data Science, NLP, Neural Networks, and LLMs
- Hands-on experience with leading LLMs (OpenAI, Gemini, Claude, Llama, Mistral, etc.)
- Deep expertise in RAG pipelines (mandatory)
- Strong proficiency in Python (mandatory)
- Experience with libraries: Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers
- Frameworks/Tools: FastAPI, LangChain, LlamaIndex, Hugging Face
- Experience with vector databases (Pinecone, Mongo Atlas, Neo4j, PG Vector)
- Knowledge of APIs, knowledge graphs, and orchestration tools
- Strong experience in MLOps, model deployment, and CI/CD pipelines
- Tools: Jenkins, GitLab CI, Azure DevOps, ArgoCD
- Experience with Kubernetes/OpenShift and cloud platforms
Responsibilities
- Design, develop, and deploy LLM-powered applications
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines
- Implement advanced prompt engineering and reusable prompt templates
- Develop agent-based AI solutions using modern frameworks
- Integrate AI solutions with enterprise systems using APIs and orchestration tools
- Work with vector databases for efficient data retrieval
- Handle large-scale unstructured data processing
- Deploy models in production using MLOps and CI/CD pipelines
- Collaborate with cross-functional teams in an Agile/Scrum environment
Skills
AIArgoCDAzure DevOpsCI/CDClaudeData ScienceFastAPIGeminiGitLab CIHugging FaceJenkinsKnowledge GraphsKubernetesLangChainLlamaLlamaIndexLLMMistralMongo AtlasNeo4jNumPyOpenAIOpenShiftOrchestration toolsPandasPG VectorPineconePyTorchPythonRAGscikit-learnTensorFlowTransformersVector databases
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