GenAI Lead

2 weeks ago

Bangalore, India HCLTech Full time

We are seeking a skilled GenAI App Lead 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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