Innovating an AI-powered natural language platform for reliable software development and infrastructure orchestration - ON-1212

Project type: Innovation
Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: Jenga AI Corp.
Project Length: Longer than 1 year
Preferred start date: As soon as possible.
Language requirement: English with some French proficiency
Location(s): ON, Canada
No. of positions: 2
Desired education level: Master'sPhDPostdoctoral fellowRecent graduate
Open to applicants registered at an institution outside of Canada: No

About the company: 

Jenga AI Corp is an AI-first platform developing and pioneering solutions that allow users to describe software application intents, and program hardware using natural language. We are focused on building reliable, production-grade systems that simplify how modern applications and AI workloads are created and deployed.

Describe the project.: 

The project focuses on developing innovative methods and systems for reliably generating, deploying, and operating complete software and infrastructure solutions using natural language interfaces and AI-driven orchestration.

The project explores how large language models (LLMs), agentic workflows, and automated infrastructure tooling can be combined to transform natural language requirements into production-ready software applications, programmed hardware, deployment pipelines, and operational environments. The project aims to improve the reliability, reproducibility, scalability, and safety of AI-assisted software generation and infrastructure automation.

Key areas of innovation include:
• AI-driven application and infrastructure generation
• Multi-agent orchestration workflows
• Automated cloud-native infrastructure automation
• Validation and testing of AI-generated outputs
• Human-in-the-loop review and correction systems
• Methods for improving determinism and reproducibility in AI-generated systems
• Integration of software and programmable hardware workflows through natural language interfaces

The candidate will assist with research, prototyping, experimentation, implementation, evaluation and improvement of orchestration techniques, deployment workflows, and AI-assisted development pipelines. Tasks may include software development, model evaluation, workflow automation, infrastructure experimentation, benchmarking, testing methodologies, and documentation.

Methodologies and technologies may include machine learning, large language models, prompt engineering, retrieval-augmented generation (RAG), distributed systems, software engineering research methods, and applied experimentation.

The intended outcome is to reduce the complexity, time, and technical barriers associated with building and operating modern software and infrastructure systems.

Required expertise/skills: 

• Python
• TypeScript / Node.js
• Go
• REST APIs and distributed systems
• Sandboxed or isolated runtime environments
• AI / Platform Tooling
• OpenAI, Anthropic, or similar AI APIs
• Structured AI workflows and orchestration systems
• Prompt engineering and LLM integration patterns
• Cloud-native architecture patterns (nice to have)