Qualitest is seeking a highly capable Full-Stack / Backend Engineer to design, build, and operate backend services and product surfaces that power internal tools and AI-driven workflows.
This role is ideal for an engineer who is practical, execution-oriented, and comfortable working across the stack from backend APIs and infrastructure to user-facing and mobile interfaces. The ideal candidate has strong experience in Python and TypeScript, and is comfortable deploying modern systems in cloud-native environments. Experience with GenAI systems, orchestration, and production pipelines is highly valued. Rust is a strong plus for performance-critical components.
Key Responsibilities
Backend Systems & APIs
- Design, implement, and maintain backend APIs and internal services using Python
- Contribute to system architecture, reliability, and maintainability
- Build integrations with internal and external systems (data, storage, authentication, services)
- Contribute to performance-sensitive backend components (Rust is a plus)
Full-Stack Product Development
- Build and maintain internal tools and user-facing interfaces using TypeScript, React, and modern web technologies
- Design polished, usable product experiences that support real workflows
- Collaborate on implementation across web and desktop environments
Mobile Development (Priority Area)
- Build or support mobile product surfaces across Android, iOS, and/or React Native
- Extend internal tools into mobile-first experiences
- Contribute to mobile UI architecture and implementation decisions
Cloud, Deployment & Infrastructure
- Deploy and operate services in cloud-native environments
- Work with:
- Kubernetes
- Terraform
- AWS CDK
- Containers / containerization
- CI/CD pipelines
- Support reliable service rollout, iteration, and operational stability
- Improve developer workflows and environment configuration
GenAI / AI Systems Integration
- Build and integrate end-to-end GenAI-enabled systems
- Support:
- Model serving and inference pipelines
- Evaluation and monitoring systems
- Workflow orchestration
- Contribute to AI-powered product capabilities such as:
- Retrieval-Augmented Generation (RAG)
- Tool / agent orchestration
- Evaluation pipelines
- Workflow automation
- Model-backed product features
Minimum Qualifications
- Strong production experience building backend systems in Python
- Proficiency in TypeScript and modern front-end development (React)
- Experience building internal tools, APIs, or product workflows end-to-end
- Hands-on experience with cloud-native engineering:
- Kubernetes
- Terraform
- AWS CDK
- Containers
- CI/CD
- Experience building or integrating GenAI systems in real-world applications
- Familiarity with:
- Model serving / inference workflows
- Evaluation / monitoring pipelines
- Orchestration systems
- RAG pipelines
- Agent-style integrations
- Strong software engineering fundamentals:
- Code quality
- Testing
- Debugging
- Performance optimization
- Maintainable system design
Preferred Qualifications
- Experience building mobile applications for:
- Experience deploying GenAI systems to production or near-production
- Strong familiarity with AI orchestration workflows
- Experience operating Kubernetes and Terraform in production
- Experience integrating with:
- Observability systems
- Security systems
- Storage systems
- Data pipelines
- Proficiency in Rust for high-performance backend systems
- Strong product instincts and ability to move from prototype production
Ideal Candidate Profile
The strongest candidates will:
- Be comfortable working as a generalist across backend, infrastructure, and UI/mobile
- Move quickly from idea to implementation
- Have a builder mindset with a focus on execution
- Be excited about modern AI and GenAI systems
- Thrive in ambiguous, high-trust environments
- Work independently while collaborating closely with small teams
What We Offer
- Contract role working at the cutting edge of AI-powered applications
- Opportunity to build across web and native platforms
- Collaboration with top-tier engineers, designers, and researchers
- Access to cutting-edge models, tools, and infrastructure
- Ability to ship impactful features quickly
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