Job description
 
                         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
 
                    
                    
Required Skill Profession
 
                     
                    
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