Senior Fullstack (Python+React/TypeScript) Developer

Our expectations of the candidate:

• Strong hands‑on experience with React for frontend development
• Solid backend development experience with frameworks such as FastAPI (priority), Flask, or Django
• Experience designing and maintaining robust, scalable APIs in production environments
• Strong experience with PostgreSQL and MongoDB, including complex queries, performance optimization, stored procedures, and views
• Practical experience with vector databases or vector search extensions (pg_vector, OpenSearch, Pinecone, or similar)
• Strong experience with AWS, including application deployment and cloud infrastructure management
• Experience with cloud‑native architectures: microservices, serverless components, containerization (Docker, Kubernetes)
• Hands‑on experience with Infrastructure as Code, preferably Terraform
• Experience with Generative AI systems, including:
  • LLM APIs (e.g., OpenAI)
  • embeddings
  • Retrieval‑Augmented Generation (RAG) pipelines
• Experience or familiarity with AI agent frameworks (e.g., LangGraph) or building agent‑based systems
• Experience with LLM orchestration platforms (e.g., AWS Bedrock) is a plus
• English: Upper-Intermediate or higher

Soft skills:

• Strong ownership mindset and accountability.
• Effective communication in cross-functional teams.
• Analytical thinking and structured problem-solving.
• attitude and continuous learning mindset.
• Ability to prioritize and work in a fast-paced environment.

Responsibilities and tasks:

• Development and maintenance of frontend functionality using React, including UI components, state management, and client‑side business logic
• Backend application development using Python (primarily FastAPI, with Flask or Django where applicable)
• Design, implementation, and maintenance of RESTful APIs and backend services used in production
• Implementation of application business logic and integrations with internal and external services
• Working with PostgreSQL (including extensions such as pg_vector) and OpenSearch / Elasticsearch for structured data and search use cases
• Integration of Generative AI capabilities into applications, including use of LLM APIs, embeddings, and Retrieval‑Augmented Generation (RAG) patterns
• Contribution to development of AI‑supported features such as intelligent search, automation, or agent‑based workflows
• Deployment and maintenance of applications in AWS, including cloud infrastructure and runtime environments
• Use of containerization and cloud‑native approaches (Docker, Kubernetes, microservices, serverless components where applicable)
• Application of software engineering best practices: code quality, testing (unit, integration, end‑to‑end), CI/CD pipelines, and observability
• Participation in system design and architectural discussions to ensure scalability, reliability, and maintainability
• Code reviews, technical documentation, and knowledge sharing within the engineering team
• Collaboration with a distributed team across multiple time zones

Send DataSend Data

Send DataSend Data

Send DataSend Data

Send DataSend Data