Python Developer

AIT Global inc.; Mississauga; On-site; CAD 110,000 - 180,000; Full time

Job summary

AIT Global inc. is seeking a Python Developer in Mississauga, ON with 8–10 years of experience in apps development or systems analysis. The role focuses on GenAI foundations, LLMs, and RAG pipelines to build production-ready AI solutions.

Responsibilities include deploying GenAI models, integrating with enterprise apps, and collaborating with cross-functional teams to deliver scalable AI capabilities.

Qualifications

• 8–10 years of experience in Apps Development or systems analysis.
• Strong knowledge of GenAI foundations, ML, data science, statistics, NLP, and AI fundamentals.
• Hands-on experience with LLMs (e.g., Google Gemini, OpenAI, Claude, Mistral, Llama) and RAG pipelines.
• Experience building, tuning, and deploying LLM-based apps using platforms like Vertex AI or Hugging Face.
• Expertise in prompt engineering, reusable templates, and agentic framework-based use cases.

Responsibilities

• Design, develop and deploy GenAI-based applications in enterprise environments.
• Build and optimize RAG pipelines and retrieval systems.
• Integrate AI models with enterprise solutions via APIs, knowledge graphs, and orchestration tools.
• Develop robust CI/CD pipelines and MLOps practices for production deployments.
• Collaborate with cross-functional teams to translate business needs into AI solutions.

Skills

Python

ML modeling

NLP

LLMs

Prompt engineering

RAG pipelines

API integration

Data processing

LangChain

LlamaIndex

Tools

Vertex AI

Hugging Face

LangChain

LlamaIndex

Kubernetes

OpenShift

Pinecone

Neo4j

Job description

Job Title: Python Developer
Location: Mississauga, ON

8-10 years of relevant experience in Apps Development or systems analysis role

Core AI/ML Foundations:

Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).

Generative AI & LLM Expertise:

• Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
• Critical: Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
• Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc.
• Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates.
• Hands-on experience with agentic framework-based use case implementation.
• Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features.

Programming & Data Engineering:

• Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex.
• Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools.
• Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval.
• Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing.

Deployment & MLOps:

• Critical: Hands-on experience deploying GenAI-based models to production environments.
• Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines.
• Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.

Cloud & Containerization:

Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment.

Soft Skills:

Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems