Generative AI Engineer

1 day ago

Hyderabad, Telangana, India Prophecy Technologies Full time ₹ 12,00,000 - ₹ 36,00,000 per year

We are seeking a highly skilled Senior AI/ML Engineer with deep expertise in Python programming, LLMs, and Generative AI ecosystems. The ideal candidate will have strong fundamentals in machine learning, deep learning, and a solid understanding of modern AI pipelines involving RAG (Retrieval-Augmented Generation), LangChain/LangGraph, document ingestion, and vector databases.

This role requires both hands-on technical expertise and strong programming discipline, with the ability to design, build, and deploy scalable AI solutions that integrate structured and unstructured data sources into real-world intelligent applications.

Roles and Responsibilities

Design, train, and fine-tune Large Language Models (LLMs) for domain-specific applications.

Implement Retrieval-Augmented Generation (RAG) pipelines for context-aware responses using enterprise data.

Work with LangChain, LangGraph, and similar frameworks to build modular, production-ready AI workflows.

Develop efficient document ingestion and vectorization pipelines to index, embed, and query knowledge bases using vector databases like Pinecone, FAISS, or Chroma.

AI/ML Engineering & Programming Excellence

Write high-quality, modular, and maintainable code in Python, applying strong software engineering principles.

Build and optimize data pipelines for feature extraction, preprocessing, and model training.

Apply deep learning and machine learning concepts for both traditional and generative use cases.

Implement prompt engineering and context optimization strategies to enhance LLM performance.

MLOps & Deployment

Develop end-to-end AI workflows with CI/CD, Docker, and Kubernetes.

Deploy models on cloud platforms (GCP Vertex AI, AWS SageMaker, Azure ML).

Monitor and optimize performance of deployed models, ensuring scalability and reliability.

Collaboration & Innovation

Collaborate with cross-functional teams to identify business use cases for AI solutions.

Research emerging LLM techniques, retrieval strategies, and framework advancements.

Mentor team members on Python best practices, AI pipeline design, and vector database integration.

Primary Skills:

Expert-level Python programming skills with solid understanding of algorithms, data structures, and OOP.

Strong understanding of LLMs (Large Language Models) and transformer-based architectures.

Hands-on experience with LangChain, LangGraph, and other LLM orchestration frameworks.

Proficiency in RAG (Retrieval-Augmented Generation) design and implementation.

Experience in document ingestion, data embedding, and vector database management (FAISS, Pinecone, Chroma, Weaviate).

Strong grounding in Deep Learning, Machine Learning, and Generative AI.

Familiarity with TensorFlow, PyTorch, and Hugging Face ecosystems.

Experience in MLOps, Docker, Kubernetes, and CI/CD pipelines for AI model deployment.

Strong knowledge of mathematical foundations linear algebra, probability, statistics.

Experience with cloud AI platforms (GCP Vertex AI, AWS SageMaker, Azure ML).

Secondary Skills:

Experience with Big Data frameworks (Hadoop, PySpark) for large-scale data processing.

Exposure to Kafka for real-time streaming data pipelines.

Knowledge of time-series forecasting techniques and applications.

Knowledge of API development for AI model serving (FastAPI, Flask).

Experience in multi-modal learning (combining text, images, video, or speech).

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