Full-Stack Developer

Own useful features end to end across Django APIs, React interfaces, data workflows and carefully chosen AI capabilities. You will work closely with a small team, take meaningful ownership and help turn real business requirements into reliable software.

What you will do

• Design and deliver complete product features across Django/DRF backends and React frontends.
• Translate business and customer needs into maintainable technical solutions.
• Design REST APIs, database models and background-processing workflows.
• Write tests, review code, debug production issues and improve performance and reliability.
• Work with PostgreSQL, Elasticsearch and cloud infrastructure as the project requires.
• Build or integrate applied AI capabilities when they create measurable user value.
• Communicate progress, technical trade-offs and risks clearly within the team and with clients.

Core requirements

• 3+ years of professional software-development experience.
• Strong Python skills and hands-on experience with Django and Django REST Framework.
• Experience designing, testing and maintaining production REST APIs.
• Practical React experience using modern JavaScript (ES6+), hooks and reusable component patterns.
• Familiarity with TypeScript or the ability to become productive with it quickly.
• Strong SQL fundamentals and experience with PostgreSQL schema design, indexes and query troubleshooting.
• Understanding of authentication, authorization and secure API development.
• Experience with automated testing, Git-based workflows and collaborative code reviews.
• Working knowledge of Docker and application deployment.
• Ability to independently break down moderately complex problems and deliver maintainable solutions.
• Clear written and verbal communication, ownership and care for product quality.

Applied AI experience - preferred

This is a full-stack engineering role with applied AI responsibilities, not a model-research position. We value practical experience shipping reliable AI-enabled software.

• Integrating an LLM or ML inference API into a production, open-source or substantial personal application.
• Structured model outputs, tool/function calling, embeddings, semantic search or retrieval-augmented generation (RAG).
• Evaluating AI output with representative test cases and measurable acceptance criteria.
• Awareness of hallucinations, prompt injection, sensitive-data exposure and unsafe model actions.
• Handling model latency, retries, rate limits, token usage, observability and cost.
• Responsible use of AI-assisted development tools, including reviewing, testing and owning generated code.
• Good judgment about when a deterministic software solution is more appropriate than AI.

Good to have

• Celery, RabbitMQ or other asynchronous processing systems.
• Elasticsearch, Redis, MySQL or MongoDB.
• AWS or GCP, CI/CD pipelines, Nginx and production observability.
• Experience with multi-tenant SaaS applications or data-intensive products.
• Pandas, scikit-learn and practical ML fundamentals such as validation, precision/recall, data leakage and model drift.
• Experience working directly with customers or converting ambiguous requirements into deliverable increments.

Tech stack

Python Django Django REST Framework React JavaScript (ES6+) TypeScript PostgreSQL REST APIs Docker Git Automated testing Applied AI / LLM APIs

Disclaimer: This job posting and location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.