Research Engineer
At a glance
Mid-level AI Research role at Rwazi, Inc. Remote · full-time.
Pay not stated Research Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Turn decision concepts into runnable prototypes, modular architectures and experimental pipelines
- Build tools to assess reasoning outputs, simulate controlled tests and benchmark decision performance
- Set up A/B tests and experiment tracking, then make research trials faster and reproducible
- Work with decision research scientists to encode models, validate concepts and surface engineering constraints
What you bring
- Strong software engineering foundations and experience creating prototypes or other experimental systems
- You can work with unclear research briefs while balancing rapid progress with technical rigor
- You understand evaluation and system validation, with familiarity in AI pipelines or decision architectures
Who this fits
This role suits a mid-level engineer focused on experimental systems for applied research, rather than product features or maintenance work. It is remote, with a flexible location.
From the employer
Research Engineer
Team: Research & Development
Location: Flexible / Remote
Reporting to: Head of R&D
Role Overview
Rwazi’s research initiatives require rapid experimentation, prototyping, and system validation.
The Research Engineer enables applied research through technical system construction.
This role builds prototypes, experimental pipelines, evaluation tooling, and research infrastructure that allow decision concepts to be tested under real-world constraints.
The Research Engineer operationalizes research velocity.
Core Mandate
The Research Engineer is accountable for:
Building research prototypes and sandbox environments
Developing evaluation tooling for decision systems
Implementing experimental system architectures
Enabling fast iteration between theory and validation
Maintaining technical research infrastructure
This role bridges conceptual research and system reality.
Key Responsibilities
Prototype Development
Implement experimental decision pipelines
Build modular, testable research architectures
Translate conceptual models into runnable systems
Research Tooling & Infrastructure
Create evaluation frameworks for reasoning outputs
Build simulation environments for controlled testing
Develop benchmarking systems for decision performance
Experiment Enablement
Implement A/B logic and structured experiment tracking
Optimize iteration cycles for research testing
Ensure reproducibility of experimental results
System Integration Support
Collaborate with Decision Research Scientists to encode models
Provide technical validation of research concepts
Identify engineering constraints early
Role Impact
Strong performance in this role results in:
Faster research iteration cycles
More reliable prototype validation
Reduced gap between research and production
Higher experimental rigor
This role accelerates Rwazi’s long-term capability development.
What This Role Is Not
This is not product feature engineering
This is not maintenance development
This is not short-term optimization
This role builds experimental systems.
Qualifications and Profile
We are looking for individuals who demonstrate:
Strong software engineering fundamentals
Experience building experimental or prototype systems
Comfort working in ambiguous research environments
Ability to balance speed and technical rigor
Familiarity with AI pipelines or decision architectures
Candidates may come from research labs, AI startups, advanced analytics teams, or system architecture roles.
How Candidates Are Evaluated
Candidates are evaluated based on:
Their ability to rapidly implement experimental systems
Technical clarity and modularity of their code
Comfort working with incomplete specifications
Understanding of evaluation logic and system validation
Ability to collaborate with research-oriented thinkers
Summary
The Research Engineer enables Rwazi’s applied decision research by building the technical infrastructure required to explore, validate, and evolve next-generation decision systems.
If you'd like, we can next define:
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