GEN AI Developer
- Mississauga, ON, Canada
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Original job description
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.
More about this job
Responsibilities
Use generative AI to accelerate requirements analysis, design, reverse engineering, development, code review, testing, and optimization for enterprise-scale projects. Build AI agents and RAG pipelines integrated with enterprise APIs, while enabling development teams and ensuring secure, compliant, and responsible AI use.
Requirements
The role requires strong Python and microservices experience, hands-on use of Claude Code and GitHub Copilot, and expertise in prompt engineering, LangChain, LangGraph, LangFlow, and agent-based architectures. Candidates should understand software design, Domain-Driven Design, cloud-native architectures, and enterprise API integration; AWS, containers, CI/CD, vector databases, and AI governance are preferred.
Skills
- Python
- Generative AI
- Prompt Engineering
- Microservices
- Claude Code
- GitHub Copilot
- LangChain
- LangGraph
- LangFlow
- Agent-Based Architectures
- Domain-Driven Design
- Enterprise API Integration
- Retrieval-Augmented Generation
- AWS Bedrock
- FastAPI
- Responsible AI
Visa sponsorship
Not detected in the job text
Categories
- Software
- Technology
- Data & Analytics
- Consulting
Keywords
- Python
- Generative AI
- Prompt Engineering
- Microservices
- Claude Code
- GitHub Copilot
- LangChain
- LangGraph
- LangFlow
- AI Agents
- Retrieval-Augmented Generation
- Enterprise APIs
- Domain-Driven Design
- Cloud-Native Architecture
- AWS Bedrock
- AWS Lambda
- Amazon S3
- DynamoDB
- PostgreSQL
- PGVector
- Docker
- CI/CD
- Vector Databases
- Embedding Models
- LLM Fine-Tuning
- FastAPI
- Anthropic APIs
- AI Governance
- Responsible AI
- Observability