Senior Backend Engineer (Go)
CloudFactory
About CloudFactory: CloudFactory is a premier, mission-driven global technology leader and data intelligence pioneer on an intensive mission to unlock the profound capabilities of artificial intelligence by transforming unstructured, unusable data into high-value training assets. By combining advanced machine learning platforms with a highly talented, globally connected network of people, CloudFactory delivers data governance and validation workflows that maximize model reliability for top AI organizations at scale. Operating as an impact-focused collective, CloudFactory is deeply committed to connecting one million people to meaningful digital work while building reflective, people-centric technology leaders worth following globally.
Position Overview
We are seeking a highly analytical, systems-minded Senior Backend Engineer (Go) to join an elite group of core technologists building our next-generation AI Data Asset Management platform in a full-time contract capacity. In this technically demanding server-side engineering seat, you will own the architectural design, implementation, and optimization of core backend services that power the platform’s massive data and workflow orchestration infrastructures. Moving far beyond boilerplate logic, you will design distributed systems in Go capable of organizing massive training datasets, tracking model version metrics, and orchestrating complex ML evaluation pipelines. This role demands a seasoned developer who excels at handling backend complexities, balancing performance thresholds, and leveraging AI-driven SDLC frameworks safely to increase development velocity.
Key Responsibilities
- High-Performance Go Development: Architect, build, and deploy high-availability backend microservices, data services, and internal infrastructure layers natively using Golang .
- Scalable API Infrastructure Design: Model and optimize low-latency REST or gRPC API contracts used by frontend web layers and distributed internal platform components.
- AI Asset Lifecycle Governance: Code core system engines designed to manage training datasets, monitor machine learning evaluation pipelines, track model metadata variations, and process human-in-the-loop review queues.
- Distributed System Triage: Conduct structural reviews across multi-tenant distributed systems, engineering defensive execution paths that eliminate runtime bottlenecks and data replication lag.
- Relational Database Management: Structure database layouts, refine transactional schemas, and optimize query performance profiles natively inside enterprise SQL engines.
- Continuous Observability Monitoring: Take full operational ownership of code post-deployment, tracking performance degradation patterns and configuring real-time telemetry metrics using Grafana .
- Automated Delivery Management: Build and scale continuous integration (CI/CD) tracks, automated script suites, and secure workload deployment frameworks across cloud systems.
Required Skills & Qualifications
- Demonstrated professional software engineering history running backend development, platform engineering, or distributed data systems architecture.
- Deep, authoritative technical command building high-concurrency backend environments natively using Golang .
- Proven background designing, documenting, and scaling enterprise-grade APIs and data flow services.
- Hands-on operational experience manipulating relational databases and crafting complex queries within SQL ecosystems.
- Strong quantitative understanding of cloud-native infrastructure automation, containerized lifecycles, and automated CI/CD workflows (AWS environments preferred).
- Practical familiarity implementing system telemetry, log management, and alerting monitors leveraging platforms like Grafana or similar.
- Demonstrated experience applying AI-assisted development tools and modern prompt utilities directly across your software development lifecycle (SDLC).
- Location Context: Contract-based parameters open to qualified backend engineers permanently residing within Romania, the United Kingdom, or Germany , with a strong hiring preference for Romania.
- Engagement Scope: Willingness to commit to a 4-month initial freelance independent contractor engagement, featuring a solid runway for extension.
Preferred Strategic Indicators (Nice to Have)
- Prior engineering experience building data platforms, analytics systems, large-scale dataset ingestion networks, or developer tools infrastructure.
- Familiarity with Python scripting, machine learning operations workflows (MLOps), or common AI/ML training platform patterns.
- Functional understanding of application security concepts, secure credential handling, and OWASP Top 10 mitigation rules.
What We Offer
- The exceptional professional canvas to directly shape architectural decisions for a high-velocity AI data asset platform used in production environments.
- Highly competitive independent contractor daily/hourly rates calibrated transparently to reflect your level of distributed systems expertise.
- Profound work-from-home remote parameters offering total lifestyle flexibility, output-driven milestones, and complete geographic freedom within supported countries.
- Integration into a globally connected, mission-driven engineering community that aggressively values technical excellence, creative innovation, and human-centric growth.
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