Senior Full-Stack Engineer (Python & JavaScript)

Bengaluru

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Client

Our client is a British bank and one of the largest finance companies in the world.

Project overview

DataArt's experts together with developers on the client's side are creating new banking apps and upgrading the old ones using the latest technology. In particular, our team is now developing a new digital portal which streamlines and automates the loan and lease management process.

Position overview

We are looking for a skilled Full-Stack Software Engineer to enhance applications with generative AI capabilities. You will integrate LLMs via Amazon Bedrock or Snowflake Cortex using Python (FastAPI) and build advanced RAG features, prompt chaining, and streaming AI responses into React UIs.

Responsibilities

Design, develop, and maintain Python backend services using FastAPI.
Integrate large language models (LLMs) into applications for AI-driven features.
Build scalable React.js frontends with functional components, hooks, and performance optimizations.
Implement retrieval-augmented generation (RAG) patterns and streaming AI responses.
Develop and consume REST and GraphQL APIs, including real-time features.
Ensure code quality with testing frameworks such as PyTest and React Testing Library.
Manage containerized deployments using Docker and orchestration tools like Kubernetes and Helm.
Apply secure development best practices including OWASP guidelines, JWT/OIDC authentication, rate limiting, and input validation.
Collaborate with cross-functional teams to define and deliver AI-enabled product features.

Requirements

4–9 years of professional development experience.
Expert-level Python (FastAPI essential; Django/Flask experience welcomed).
Strong modern JavaScript/TypeScript and deep React.js expertise (functional components, hooks, context, custom hooks, performance optimisation).
Experience building and consuming REST/GraphQL APIs and real-time features.
Solid understanding of testing: PyTest, Playwright/Cypress, React Testing Library.
Containerisation & orchestration: Docker, Kubernetes, Helm.
Secure development practices (OWASP, JWT/OIDC, rate limiting, input validation).

Nice to have

Hands-on experience integrating LLMs into web applications (Amazon Bedrock, Snowflake Cortex, LangChain/LlamaIndex in Python).
Building RAG-based features (vector stores, semantic search, streaming responses in React).
Previous work on AI-powered chat/assistant interfaces or document intelligence.
AWS services: Lambda, API Gateway, Step Functions, EventBridge.
Experience with LLM APi/MCP.
Event-driven architecture and Kafka.
Financial services or regulated environment experience.

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Zgodnie z oficjalnym kalendarzem, niezależnie od kalendarza klienta

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