GenAI Lead

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