GEN AI Developer

Role Name

GEN AI Developer

Location

Mississauga, ON CAN

JOB DESCRIPTION

• Min 6 years of experience in Python/Microservices development.
• Experienced professional with strong Python development and Generative AI expertise, especially in prompt engineering.
• 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.

Soft Skills

• Strong leadership and mentoring abilities.
• Excellent communication and collaboration skills.
• Ability to drive innovation and evangelize GenAI adoption across teams.