GenAI App Developer

3 days ago

bangalore, India HCLTech Full time

Job Overview: We are seeking a skilled GenAI App Developer (or Full Stack Developer , Python Backend Developer , API Developer , Prompt Engineer ) with expertise in API development , backend logic , machine learning , and NLP to contribute to large-scale GenAI applications . You'll work on API integrations , system performance optimization, and developing multi-agent workflows, all within a dynamic, collaborative environment. Required Qualifications: Proven experience in API development (e.g., FastAPI , Flask , Django ). Strong knowledge of Python , machine learning (PyTorch ), and NLP (e.g., spaCy ). Expertise in API authentication (OAuth, API keys ) and API documentation (Swagger). Experience with task queues (Celery ) and multi-agent workflows . Hands-on experience with databases (MySQL, PostgreSQL , BigQuery , NoSQL ). Familiarity with caching (Redis, Memcached) and cloud platforms (AWS , Google Cloud , Azure ). Key Responsibilities: API Integration & Development: Identify and define API integration points , ensuring clear documentation. Design, implement, and test API endpoints (e.g., /generate, /status). Auto-generate API documentation using FastAPI & Swagger . Implement rate limiting (Flask-Limiter ) and authentication (OAuth , API keys ). LLM & NLP Integration: Develop prompting logic for Large Language Models (LLMs) to ensure accurate responses. Integrate machine learning frameworks (e.g., PyTorch ) and NLP libraries (e.g., spaCy ). Design and implement multi-agentic workflows using patterns like actor model , publish-subscribe , and client-server . Multi-Agentic System Design: Build and coordinate multi-agentic systems , ensuring efficient task delegation, communication, and failure handling across agents. Develop distributed task management using tools like Celery and Kubernetes . Testing & Debugging: Write unit/integration tests with Pytest . Set up logging and monitoring for system health and debugging. Database & Caching: Integrate with MySQL , PostgreSQL , NoSQL (e.g., BigQuery , MongoDB ), and vector databases (e.g., Pinecone ). Implement caching strategies (e.g., Redis , Memcached ) to optimize performance. Security & Compliance: Ensure secure API access and data protection (OAuth, API keys , input validation). Highly Desirable Qualifications: Experience with vector databases (e.g., Pinecone , Weaviate, Cloud-based AI search (Azure AI Search ). Knowledge of CI/CD pipelines and containerization (e.g., Docker , Kubernetes ). Familiarity with API design tools (e.g., Postman ) and rate limiting (Flask-Limiter ). Tools & Technologies: API Frameworks : FastAPI , Flask , Django Machine Learning & NLP : PyTorch , spaCy Task Management : Celery Databases : MySQL , PostgreSQL , BigQuery , MongoDB , Pinecone , Weaviate Caching : Redis , Memcached Cloud Platforms : AWS , Google Cloud , Azure Version Control : Git Security & Monitoring : OAuth , API keys , Python logging module

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