Pay Range: $55.00hr - $60.00hr

Job Overview:

The ideal candidate has 10+ years of experience in Python and microservices development. This role requires an experienced professional with strong Python development expertise and deep specialization in Generative AI, particularly in prompt engineering.

Core Responsibilities:

- Leverage Generative AI to accelerate requirement gathering, requirement analysis, and high-level/low-level design creation.
- Perform reverse engineering of existing enterprise-scale applications to auto-generate architecture diagrams, data flow diagrams, and sequence diagrams across codebases including Python, Java, Angular, and Mule.
- Accelerate design creation using Generative AI by proposing API specifications and applying Domain-Driven Design (DDD) patterns.
- Utilize Claude Code, GitHub Copilot, and similar AI tools for Pull Request reviews, automated test generation, software development, code refactoring, and code optimization.
- Build and deploy AI agents using LangChain, LangGraph, and LangFlow integrated with enterprise APIs.
- Implement Retrieval-Augmented Generation (RAG) pipelines for knowledge-driven applications.
- Lead and enable development teams to effectively use Generative AI tools, driving prompt engineering best practices and Generative AI use case adoption.




- Conduct workshops and training sessions for developers on Generative AI tools and frameworks.
- Ensure security, compliance, and responsible AI usage across all Generative AI implementations.

Must-Have Skills:
- Strong proficiency in Python and microservices development.
- Hands-on experience with Claude Code, GitHub Copilot, and prompt engineering.
- Expertise in LangChain, LangGraph, LangFlow, and agent-based architectures.
- Solid understanding of software design principles, Domain-Driven Design (DDD), and cloud-native architectures.
- Experience building AI solutions integrated with enterprise APIs.

Preferred Skills:

- Familiarity with AWS services including Bedrock, Lambda, S3, DynamoDB, and Postgres/PGVector.
- Knowledge of containerization technologies such as Docker and CI/CD pipelines.
- Experience with vector databases, embedding models, and Large Language Model (LLM) fine-tuning.
- Understanding of AI governance, bias mitigation, and responsible AI frameworks.
- Proficiency with FastAPI, Anthropic APIs, and observability tools for AI workflows.

Soft Skills:

- Solid leadership and mentoring abilities.
- Excellent communication and presentation skills.
- Ability to communicate effectively with stakeholders, drive innovation, and evangelize Generative AI adoption across teams.

📌 Senior Generative AI Developer (Mississauga)
🏢 Cynet Systems
📍 Mississauga