Senior Full Stack Engineer - AI

New

Based in South AfricaFull-TimeSenior

Salary not disclosed

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Job Details

Experience: Several years
Required Skills: AWSNode.jsPostgreSQLExpress.jsTypeScriptNext.jsTerraformPrompt Engineering

Several years of professional software engineering experience with strong expertise in TypeScript and Node.js.
Strong PostgreSQL expertise, including JSONB, query performance optimization, and database migrations.
Demonstrated full-stack development experience across technologies such as Next.js 15, React Query, Express, and BullMQ.
Practical experience with AWS services including ECS and RDS, as well as infrastructure-as-code using Terraform.
Hands-on experience building, deploying, monitoring, and operating AI/LLM-powered applications and pipelines in production.
Strong understanding of prompt engineering, context management, model selection, cost considerations, and AI evaluation methodologies.
Experience working with multiple AI providers and understanding how to design flexible, production-ready AI architectures.
Strong debugging instincts and the ability to investigate and resolve issues in live production systems.
Exceptional autonomy and ownership, with the ability to identify problems, develop solutions, and execute independently.
Usability-first mindset and ability to create effective end-user interfaces.
AI-native approach to software development, with familiarity using tools such as Claude Code or Cursor.

Build and ship end-to-end product features independently, including user-facing interfaces, backend services, infrastructure, and AI-powered functionality.
Work across the full technology stack to translate real user needs into practical, scalable product solutions.
Collaborate directly with domain experts and users to identify problems, validate solutions, and improve workflows.
Develop intuitive interfaces with a strong usability-first mindset.
Own technical problems from initial discovery through development, deployment, monitoring, and production resolution.
Advance AI capabilities through prompt engineering, context management, model selection, and multi-provider AI architectures.
Build and operate production AI pipelines using providers such as AWS Bedrock, Anthropic, and OpenAI.
Monitor, debug, and improve live production environments using Sentry, CloudWatch, and PostgreSQL performance monitoring.
Contribute to AWS infrastructure, including ECS and RDS, while maintaining strong standards for reliability, scalability, and performance.

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