Technical Co-Founder - Graph ML, GNNs & Program Analysis
rkitoTechnical Co-Founder
rkito | Mississauga, Ontario | Full-time, On-site & Remote
rkito is building infrastructure and protocols for trustworthy, design-conformant Agentic Engineering at enterprise scale.
The company is pioneering Design Continuity, a discipline that keeps autonomous software systems aligned with an organization’s architecture, standards, business rules, and security boundaries.
rkito integrates into existing software delivery workflows and CI/CD pipelines to continuously verify design conformance across the software lifecycle - another concept we are pioneering, Continuous Design Audit. By auditing changes against design intent, rkito helps organizations detect architectural drift early, reduce engineering risk, and maintain alignment with enterprise requirements.
Our vision is to keep humans in control while autonomous systems operate with speed, consistency, accountability, and transparent engineering decisions.
We are looking for a Technical Co-Founder to help define and build the technical foundation of rkito.
This is a founder-level role for someone who wants to work at the intersection of AI, software engineering, program analysis, and systems research—and who is motivated by the opportunity to create a new technical discipline rather than simply build another ML product.
You will lead the development of the core intelligence behind Design Continuity, while also helping shape the company's broader technical direction, product evolution, research agenda, and engineering organization.
The role will involve developing graph-based representations of software and architecture, researching Graph ML and program-analysis approaches, and turning those ideas into production systems that can operate on large and continuously changing software environments.
Just as importantly, you will work closely with the founder, researchers, engineers, early adopters, and strategic partners to determine what should be built, why it matters, and how to turn technically difficult ideas into something enterprises can actually adopt.
- Define the technical vision and architecture for rkito's core intelligence platform.
- Lead research into graph-based representations of software, architecture, and design intent.
- Develop scalable approaches for understanding large, heterogeneous software systems.
- Translate research ideas into working prototypes and eventually production systems.
- Establish the technical roadmap and make foundational technology decisions.
- Work with researchers and academic collaborators to explore new approaches.
- Work directly with early customers and design partners to validate technical assumptions and shape the product.
- Participate in technical discussions, demonstrations, partnerships, and customer engagements.
- Help communicate rkito's technical vision to engineers, researchers, customers, partners, and investors.
- Build and mentor the initial engineering and research team as the company grows.
- Contribute to product strategy and company-building decisions as a member of the founding team.
The role requires significant depth in Machine Learning and Graph-based AI, particularly where these technologies intersect with software engineering.
Relevant experience includes:
- Graph Neural Networks and Graph ML
- Heterogeneous and relational graph learning
- Graph representation learning
- Graph partitioning, decomposition, and large-scale graph processing
- Program analysis and software representations
- Code Property Graphs, AST, CFG, PDG, or related representations
- ML for code / neural program analysis
- Distributed or large-scale ML systems
- Model training, evaluation, and production deployment
Experience with technologies such as PyTorch, PyTorch Geometric, DGL, C++, Rust, Go, CUDA, or similar systems is valuable, but the underlying technical understanding matters more than any particular framework.
We are particularly interested in people who have tackled problems involving large, heterogeneous, dynamic graphs and understand the challenges of making graph-based learning computationally scalable.
We are looking for someone who combines technical depth with founder-level ownership.
You should be:
- Technically curious — willing to go beyond established approaches and investigate difficult problems from first principles.
- Research-oriented — able to read papers, formulate hypotheses, run experiments, and distinguish promising ideas from attractive theory.
- Product-minded — able to translate technical capabilities into something customers genuinely need.
- Entrepreneurial — comfortable operating without a predefined roadmap and making decisions with incomplete information.
- Customer-oriented — willing to engage directly with early adopters and understand their problems firsthand.
- Communicative — able to explain complex technical concepts clearly to engineers, executives, customers, researchers, and investors.
- Collaborative — capable of working across research, engineering, product, and business functions.
- A builder — someone who enjoys taking an idea from research → prototype → production.
- A leader — prepared to eventually build and lead the research and engineering organization.
You should be comfortable contributing outside a narrowly defined technical role. In an early-stage company, that may mean participating in a customer discussion one day, reviewing a research paper the next, designing an experiment, helping shape product strategy, or recruiting the next engineer.
rkito is not simply applying an existing ML model to software.
We are exploring a fundamental question:
How can an autonomous software engineering system continuously understand and respect the design intent of the organization it is operating within?
That requires connecting software structure, architecture, organizational knowledge, design intent, and machine learning into a scalable technical system.
The person joining as Technical Co-Founder will have the opportunity to help define that architecture and, potentially, an entirely new category of infrastructure for autonomous software engineering.
Required
- Deep hands-on experience in Machine Learning / Deep Learning.
- Strong understanding of Graph ML and/or Graph Neural Networks.
- Strong analytical and problem-solving ability.
- Experience taking research or experimental ideas through implementation.
- Strong software engineering capability.
- Ability to operate independently in an early-stage environment.
- Strong written and verbal communication.
Highly valued
- Heterogeneous GNNs or relational graph learning.
- Graph partitioning and scalable graph computation.
- Program analysis, compilers, or software architecture.
- ML for code or neural program analysis.
- Large-scale or distributed ML systems.
- Academic research experience, publications, or significant independent research.
- Experience building products or companies.
- Experience working directly with enterprise customers or technical partners.
A PhD is not required. Demonstrated technical depth, original thinking, and the ability to build matter more than credentials.
This is a founding position, not a conventional engineering job.
You will have meaningful ownership over the technical direction of the company and the opportunity to help build the research, product, and engineering organization from the ground up.
If you are interested in solving difficult problems at the intersection of AI, software engineering, graph intelligence, and autonomous systems, we'd like to hear from you.
- Full-time · On-site & Remote · Mississauga, Ontario