Python-GenAI-LLMOps

Key Responsibilities:

Develop and deploy Generative AI applications using LLMs (GPT, Llama, etc.)
Build and maintain LLM pipelines, including prompt engineering and fine-tuning
Design and implement end-to-end AI/ML workflows (data → model → deployment)
Work with vector databases for semantic search and retrieval (RAG architecture)
Implement LLMOps practices for monitoring, evaluation, and versioning
Integrate LLMs into applications via APIs and microservices
Optimize model performance, cost, and latency
Collaborate with data engineers, product teams, and stakeholders
Conduct testing, validation, and debugging of AI models
Ensure security, compliance, and responsible AI practices

Required Skills & Qualifications:

Technical Skills:

Strong proficiency in Python:

Hands-on experience with Generative AI & LLM frameworks:

OpenAI / Azure OpenAI APIs

Hugging Face Transformers:

Lang Chain / Llama Index

Experience with prompt engineering and RAG (Retrieval-Augmented Generation)
Familiarity with vector databases (FAISS, Pinecone, Weaviate, Chroma)
Knowledge of ML/DL frameworks (Py Torch / Tensor Flow – basics)
Experience in API development (FastAPI, Flask)
Understanding of RESTful services and microservices architecture

• Primary skills:Technology->Data Science->Machine Learning,Technology->Geographical Information System->Spatial Databases->SQL Server,Technology->Machine Learning->Python

Preferred Skills (Nice-to-Have)

Experience with fine-tuning LLMs / parameter-efficient tuning (LoRA, PEFT)
Knowledge of multimodal AI (text, image, audio)
Exposure to cloud platforms (AWS, Azure, GCP)
Experience with Kubernetes and scalable deployments
Knowledge of data engineering tools (Spark, Kafka)
Familiarity with vector search optimization and embeddings
Understanding of AI governance, ethics, and compliance
Experience with chatbots, copilots, or conversational AI systems

Education: MCA,MSc,MTech,Bachelor of Engineering,BCA,BSc,BTech

Preferred skills: Technology->AI-Data science->Machine Learning,Technology->AI-Data science->PYTHON,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)