Python Developer – GenAI / LLM Specialist

Job Description

Python Developer – GenAI / LLM Specialist

Job Summary :

We are seeking a highly skilled Python Developer with hands-on experience in Generative AI (GenAI) and Large Language Models (LLMs). The ideal candidate will be responsible for leveraging GenAI to improve development productivity, optimize data workflows, and integrate AI capabilities into enterprise applications.

Key Responsibilities :

Design and develop scalable Python-based solutions integrating Generative AI and LLMs for enhancing development productivity.

Build and integrate REST / GraphQL APIs to connect LLMs with enterprise systems.

Develop, refine, and implement prompt engineering techniques to optimize LLM performance and accuracy.

Perform data preprocessing and create high-quality embeddings to support AI / ML pipelines.

Evaluate LLM performance in terms of accuracy, latency, and cost; recommend and implement optimizations.

Support fine-tuning and model customization to align with specific enterprise requirements and use cases.

Work with vector databases to support efficient semantic search and data retrieval.

Ensure compliance with AI safety, security, and ethical considerations, including hallucination mitigation, bias detection, and data privacy.

Primary Skills :

Python Development : Strong programming skills with proven experience building scalable, production-ready applications.

LLM Experience : Practical experience with LLMs (e.g., OpenAI GPT, Claude, Mistral) including integration, tuning, and evaluation.

Prompt Engineering : Deep understanding of prompt design and optimization strategies.

API Development : Experience with REST and GraphQL API integration.

Data Engineering : Proficiency in data preprocessing, manipulation, and transformation for AI use cases.

Secondary Skills :

Embeddings & Vector Search : Knowledge of creating and using embeddings for search and recommendation systems.

Model Fine-tuning : Experience in customizing and fine-tuning open-source or proprietary LLMs.

Performance Evaluation : Ability to measure and optimize LLM performance (latency, accuracy, and cost).

Vector Databases : Familiarity with tools like FAISS, Pinecone, Weaviate, or similar.

Good to Have Skills :

AI / ML Compliance : Understanding of AI safety, security, and governance frameworks.

Cloud Platforms : Exposure to deploying AI solutions on cloud platforms such as AWS, GCP, or Azure.

DevOps Practices : Familiarity with CI / CD pipelines and containerization (Docker / Kubernetes).

Visualization Tools : Ability to present data and model insights using dashboards (e.g., Streamlit, Dash, or similar).

Skills : Python,Artificial Intelligence,Prompt,Rest Api

Requirements

Python