Technology, Information and Internet · 4.4k people
Lead Backend Engineer - AI Tooling
Posted 2 Nov
What’s this role about? Lead the design, development, and optimization of Python backend systems, data pipelines, annotation tools, APIs, and evaluation infrastructure for AI model training and assessment. Improve production system reliability, performance, and safety, and guide architecture decisions through design and code reviews with cross-functional teams.
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Company
About Alignerr We're looking for experts to help train better AI. At Alignerr, we offer paid, flexible projects for writers, coders, and subject matter experts to refine and align advanced artificial intelligence. Work when you want, where you want. Apply today at Alignerr.com or through our open Job Postings.
Responsibilities
- Design, build, and optimize high-performance Python systems supporting AI data pipelines and model evaluation workflows
- Develop backend services and full-stack tooling for large-scale data annotation, validation, and quality control
- Architect robust APIs (REST/GraphQL), design database schemas, and implement authentication and authorization flows
- Improve reliability, performance, and safety across existing Python codebases
- Identify bottlenecks and edge cases in data and system behavior, then implement scalable, production-ready fixes
- Collaborate with data, research, and engineering teams across model training and evaluation workflows
- Lead synchronous design and code reviews — driving decisions that shape the architecture of critical AI systems
Qualification
Required
- Native or fluent English speaker with strong written and verbal communication skills
- Full-stack developer with a deep systems programming background and 5+ years writing production Python backend services
- Fluent in modern Python web frameworks with strict type enforcement patterns
- Experienced architecting scalable APIs, data schemas, and auth systems in production environments
- A natural leader in code reviews and system design sessions — you can articulate decisions clearly and bring others along
- Able to commit 20–40 hours per week on a reliable, ongoing basis
Preferred
- Prior experience with data annotation, data quality pipelines, or AI evaluation systems
- Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
- Experience with distributed systems, developer tooling, or platform engineering
Benefits
- Work directly with leading AI labs on systems that influence next-generation model development
- Fully remote and flexible — work from wherever you do your best work
- Freelance autonomy with the structure and stability of ongoing, project-based engagement
- Make a real, measurable impact on the infrastructure behind some of the most advanced AI in the world
- Potential for extended engagement and expanded scope as projects grow
Interested in this role?
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