Job Description:
The Gen AI App Developer will design, develop, and maintain applications integrating Large Language Models (LLMs) and AI-driven workflows. The role involves API development, multi-agentic system design, database and caching strategies, and implementing secure, scalable, and high-performance AI applications. Requirement/Must Have:
Proven experience in API development using FastAPI, Flask, or Django. Strong proficiency in Python and experience with machine learning frameworks (e.g., PyTorch). Hands-on experience with NLP libraries such as spaCy. Expertise in API authentication methods (OAuth, API keys) and API documentation (Swagger). Experience with task queues (Celery) and multi-agent workflow design. Database experience: MySQL, PostgreSQL, BigQuery, NoSQL (MongoDB). Familiarity with caching technologies (Redis, Memcached). Experience with cloud platforms (AWS, Google Cloud, Azure). Experience:
Design, implement, and maintain API endpoints, with auto-generated documentation. Develop prompting logic and integrate LLMs for accurate responses. Build and coordinate multi-agentic systems using patterns like actor model, publish-subscribe, and client-server. Implement distributed task management and failure handling. Write unit and integration tests using Pytest; set up logging and monitoring. Implement caching strategies and optimize performance for high-volume AI workloads. Ensure secure API access and data protection. Responsibilities:
Identify and define API integration points and maintain clear documentation. Integrate machine learning and NLP libraries into AI workflows. Build multi-agent systems and manage distributed task execution. Set up monitoring, logging, and debugging for AI applications. Implement security, authentication, and xx-limiting for APIs. Collaborate with cross-functional teams to deliver scalable AI solutions. Skills:
Strong Python programming and ML/NLP knowledge. Expertise in API frameworks and documentation. Experience with multi-agent systems and distributed task management. Database management and caching strategies. Familiarity with cloud computing, CI/CD pipelines, and containerization (Docker, Kubernetes). Knowledge of vector databases (e.g., Pinecone, Weaviate) is a plus. Qualification And Education:
Bachelor's or Master's degree in Computer Science, Software Engineering, AI, or related field. Proven hands-on experience in AI application development, API design, and ML/NLP integration. Familiarity with version control systems (Git) and security/compliance best practices.
The Gen AI App Developer will design, develop, and maintain applications integrating Large Language Models (LLMs) and AI-driven workflows. The role involves API development, multi-agentic system design, database and caching strategies, and implementing secure, scalable, and high-performance AI applications. Requirement/Must Have:
Proven experience in API development using FastAPI, Flask, or Django. Strong proficiency in Python and experience with machine learning frameworks (e.g., PyTorch). Hands-on experience with NLP libraries such as spaCy. Expertise in API authentication methods (OAuth, API keys) and API documentation (Swagger). Experience with task queues (Celery) and multi-agent workflow design. Database experience: MySQL, PostgreSQL, BigQuery, NoSQL (MongoDB). Familiarity with caching technologies (Redis, Memcached). Experience with cloud platforms (AWS, Google Cloud, Azure). Experience:
Design, implement, and maintain API endpoints, with auto-generated documentation. Develop prompting logic and integrate LLMs for accurate responses. Build and coordinate multi-agentic systems using patterns like actor model, publish-subscribe, and client-server. Implement distributed task management and failure handling. Write unit and integration tests using Pytest; set up logging and monitoring. Implement caching strategies and optimize performance for high-volume AI workloads. Ensure secure API access and data protection. Responsibilities:
Identify and define API integration points and maintain clear documentation. Integrate machine learning and NLP libraries into AI workflows. Build multi-agent systems and manage distributed task execution. Set up monitoring, logging, and debugging for AI applications. Implement security, authentication, and xx-limiting for APIs. Collaborate with cross-functional teams to deliver scalable AI solutions. Skills:
Strong Python programming and ML/NLP knowledge. Expertise in API frameworks and documentation. Experience with multi-agent systems and distributed task management. Database management and caching strategies. Familiarity with cloud computing, CI/CD pipelines, and containerization (Docker, Kubernetes). Knowledge of vector databases (e.g., Pinecone, Weaviate) is a plus. Qualification And Education:
Bachelor's or Master's degree in Computer Science, Software Engineering, AI, or related field. Proven hands-on experience in AI application development, API design, and ML/NLP integration. Familiarity with version control systems (Git) and security/compliance best practices.