Role Name: GEN AI Developer
Location: Mississauga, ON -Hybrid
JOB DESCRIPTION
Experienced professional with strong Python development and Generative AI expertise, especially in prompt engineering.
Key Responsibilities
Leverage GenAI to accelerate:
- Requirement gathering and analysis.
- Design creation (HLD/LLD).
- Reverse engineering of existing applications.
- Development for enterprise-scale projects.
- Lead and enable development teams to effectively use GenAI tools and frameworks.
- Reverse engineer application codebases (Python, Java, Angular, Mule) to auto-generate:
- Architecture diagrams.
- Data flow and sequence diagrams.
- Accelerate design creation using GenAI:
- Propose API specifications.
- Apply Domain-Driven Design (DDD) patterns.
- Utilize Claude Code, GitHub Copilot, and similar tools for:
- Pull Request reviews.
- Automated test generation.
- Development, Code refactoring and optimization.
- Build and deploy AI agents using LangChain, LangGraph, integrated with enterprise APIs.
- Implement RAG (Retrieval-Augmented Generation) pipelines for knowledge-driven applications.
- Drive prompt engineering best practices and GenAI use case adoption across teams.
- Conduct workshops and training sessions for developers on GenAI tools and frameworks.
- Ensure security, compliance, and responsible AI usage in all GenAI implementations.
Must-Have Skills
- Strong proficiency in Python and microservice 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, DDD, and cloud-native architectures.
- Experience building AI solutions integrated with enterprise APIs.
Preferred Skills
- Familiarity with AWS services (Bedrock, Lambda, S3, DynamoDB, Postgres/PGVector).
- Knowledge of containerization (Docker) and CI/CD pipelines.
- Experience with vector databases, embedding models, and LLM fine-tuning.
- Understanding of AI governance, bias mitigation, and responsible AI frameworks.
- Proficiency with FastAPI, LangChain, LangGraph, Bedrock, Anthropic APIs.
- Experience with observability tools for AI workflows.
