Write secure, production-quality code using PHP, JavaScript, SQL and No SQL databases, Linux, Docker, and Apache in an open-source development environment
Job Description
Responsibilities
Write secure, production-quality code using PHP, JavaScript, SQL and No SQL databases, Linux, Docker, and Apache in an open-source development environment
Write automated tests such as unit, acceptance, and integration tests to ensure high-quality code.
Develop SQL and No SQL database schemas and write code to work with databases.
Work with Architect to design and implement AWS cloud-native solutions using technologies such as AWS S3, SNS, SES, SQS, and ElasticBeanstalk.
Perform code review on peer’s code.
Deploy code to production servers using a CI/CD pipeline using Gitlab and AWS ECR.
Participate in an agile development team.
Qualifications
Bachelor’s Degree in Information Technology or related field or commensurate experience
5 years’ experience with open-source web application development with a combination of the following:
Experience developing full stack, open-source applications using Linux, Apache, PHP, SQL and No SQL databases, JavaScript, Node.js, and Docker.
Experience using Git or other source control for code management.
Experience with JavaScript framework React and PHP framework Laravel.
Knowledge of OWASP and other web security best practices.
Experience with modern web development technologies such as REACT, ES6, Responsive Design.
Specializes in retrieval-augmented generation architecture — building the search, indexing, and retrieval layer that grounds LLM outputs in accurate, up-to-date information.
Works on pretraining and post-training of foundation models — architecture experiments, training efficiency, alignment techniques (RLHF, DPO), and scaling research, often in collaboration with research scientists.
Owns model development, training, and quality — building and improving the ML models (not just LLM wrappers) that power a product, from data pipeline to production deployment.
Owns the compute infrastructure that trains and serves AI models — GPU cluster management, distributed training pipelines, and inference serving at scale. A natural pivot for DevOps/backend infra engineers.
