
Generative AI Developer
1 day ago
About the Role :
We are seeking an experienced Python and Generative AI Developer to design, develop, and deploy intelligent AI-driven solutions.
The ideal candidate will have strong expertise in Python backend frameworks, Natural Language Processing (NLP), and hands-on experience with Generative AI models (LLMs).
This role involves working on end-to-end AI pipelines, integrating APIs, and collaborating with cross-functional teams to deliver scalable and impactful applications.
Key Responsibilities :
- Develop and maintain scalable backend applications using Python, Flask, and FastAPI.
- Design, integrate, and fine-tune Generative AI solutions leveraging LLMs (GPT, LLaMA, Claude, etc.
- Build and optimize data pipelines using Pandas, NumPy, and SQL.
- Architect and implement APIs/services to seamlessly interface applications with GenAI models.
- Manage and query databases (SQL and MongoDB) for structured and unstructured data storage.
- Apply advanced NLP algorithms such as Named Entity Recognition (NER), document classification, and sentiment analysis.
- Implement prompt engineering and build RAG (Retrieval-Augmented Generation) pipelines.
- Work with vector databases (FAISS, Pinecone, Chroma) for embedding and retrieval tasks.
- Collaborate with product, data science, and DevOps teams for smooth deployment of AI-powered solutions.
- Ensure scalability, performance, and reliability of deployed AI systems.
Required Skills & Qualifications :
- Strong proficiency in Python, with production experience using Flask and FastAPI.
- Solid expertise in Pandas, NumPy, and SQL for data handling and transformations.
- Hands-on experience with MongoDB and schema design.
- Proven experience in working with LLMs (OpenAI, Hugging Face, Anthropic APIs, etc.
- Strong understanding of NLP tasks (NER, text classification, sentiment analysis, summarization).
- Familiarity with AI/ML libraries such as SpaCy, Hugging Face Transformers, and LangChain.
- Experience with vector databases for semantic search and retrieval-based workflows.
- Proficiency in RESTful API development and integration.
- Knowledge of Git, Docker, and CI/CD pipelines for collaborative development.
- Exposure to cloud platforms (AWS, GCP, or Azure) and MLOps tools.
Preferred Qualifications :
- Experience in fine-tuning or training LLMs.
- Familiarity with Kubernetes and container orchestration.
- Knowledge of data security and compliance in AI workflows.
- Strong problem-solving, analytical, and communication skills
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