Full-Stack Software Engineer – Distributed Systems & AI

Key Responsibilities

Design, develop, and maintain scalable, secure, and high-performance full-stack applications.

Build distributed backend services, microservices, and RESTful APIs.

Develop backend systems using Python frameworks such as FastAPI and Django, and Node.js.

Build responsive, performant frontend applications using React and Next.js.

Design and optimize relational, NoSQL, and vector database systems.

Develop AI-powered applications using LLMs, RAG architectures, embeddings, semantic search, and vector databases.

Integrate third-party APIs, AI models, external services, and data processing pipelines.

Implement authentication, authorization, caching, asynchronous processing, and background jobs.

Write clean, modular, reusable, testable, and maintainable code.

Apply appropriate design patterns, OOP principles, SOLID principles, and software architecture best practices.

Perform code reviews, debugging, performance optimization, testing, and production troubleshooting.

Collaborate with product, data, and engineering teams to deliver reliable software solutions.

Required Skills

Programming: Strong Python and JavaScript/TypeScript.

Backend: FastAPI, Django, Node.js, REST APIs, microservices, distributed systems, and asynchronous programming.

Frontend: React, Next.js, HTML5, CSS3, responsive design, and frontend state management.

Databases: PostgreSQL, MySQL, MongoDB, Redis, and experience with database design, indexing, transactions, and query optimization.

Vector Databases & AI: Qdrant, Pinecone, Weaviate, Chroma, or FAISS; embeddings, semantic search, RAG pipelines, and LLM API integration.

Engineering Fundamentals: OOP, SOLID principles, design patterns, data structures, algorithms, clean code, and system design.

Distributed Systems: Message queues, event-driven architecture, caching, concurrency, fault tolerance, and scalable service communication.

DevOps & Deployment: Git, Docker, CI/CD, Linux, logging, monitoring, and cloud deployment fundamentals.

Testing & Security: Unit testing, integration testing, API testing, secure coding, and authentication/authorization.

Good to Have

Experience with machine learning, deep learning, NLP, and AI frameworks such as PyTorch or TensorFlow.

Knowledge of LangChain, LlamaIndex, model serving, and agentic AI workflows.

Experience with Kafka, RabbitMQ, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.

Familiarity with GraphQL, WebSockets, observability tools, and infrastructure as code.

Experience optimizing application latency, throughput, scalability, and cloud infrastructure costs.

Qualifications

Bachelor’s degree in Computer Science, IT, Engineering, or equivalent practical experience.

Ideal Candidate:

An engineering-focused full-stack developer capable of designing distributed backend systems, building modern frontend applications, working across different database technologies, and developing AI-powered products using LLMs and RAG architectures.

Skills: typescript,next.js,large language models (llms),retrieval-augmented generation (rag),microservices,fastapi,react.js,python,postgresql,rest apis