Python + GenAI

Job Description

Key Responsibilities :

Generative AI Development

• Develop and implement generative AI models using frameworks like LangChain

or Llama-Index.

optimal LLM responses for diverse use cases.

hyperparameter tuning, and response caching.

vector databases like Pinecone, Weaviate, Supabase, or PGVector for efficient

similarity searches.

personalized query resolution.

and generation.

ensure system reliability.

Backend Engineering

FastAPI, Django, or Flask.

systems and services.

and integrate vector databases (Pinecone, PGVector, Weaviate, Supabase) for

advanced AI workflows.

maintainable, high-quality code.

with external systems.

supporting text, image, and video workflows.

equivalent job queuing systems.

deployments.

best practices.

Qualifications : Essential :

frameworks like FastAPI, Django, or Flask.

or similar tools, with experience in prompt engineering and Retrieval-Augmented

Generation (RAG).

MySQL) and vector databases (Pinecone, Weaviate, Supabase, PGVector) for

embeddings and similarity search.

multimodal AI applications involving text, images, or video.

environments using Docker and managing pipelines for scalability and reliability.

integration tests (e.g., Pytest), along with application debugging and

performance optimization.

concepts for handling concurrent tasks efficiently.

Preferred :

serverless applications and VM setups.

frameworks like Angular or React for better collaboration with frontend teams.

evaluate LLM performance in real-time.

AI applications and advanced agentic workflows.

hardening.

technologies are a plus.

Requirements

Requirements

SAP CX, SAP Customer Experience, SAP CX Analytics, Sales Cloud, Service Cloud, Marketing Cloud, Commerce / Hybris Cloud, SAP CX Integartions, SAP S / 4 HANA, SAP ECC, SAP CPI