Generative AI Engineer - LLM Models

Job Description : Gen AI Engineer

Location : Bangalore / Hyderabad

Experience Required : 5 to 14 years

Notice Period : Up to 60 Days

Interview Mode : Face-to-Face (2 Rounds)

Interview Date : 13th December 2025

Position Overview :

We are seeking a highly skilled Gen AI Engineer with strong hands-on experience in Generative AI, Machine Learning, and NLP. The ideal candidate will be responsible for building, optimizing, and deploying scalable AI/ML solutions, integrating GenAI capabilities into business applications, and collaborating with cross-functional teams to drive innovation.

Key Responsibilities

- Design, build, and implement Generative AI models for real-world use cases.

- Develop and optimize Machine Learning algorithms and pipelines.

- Work extensively with NLP techniques, including text classification, summarization, embeddings, and LLM fine-tuning.

- Evaluate and experiment with AI/LLM platforms, understanding their strengths, limitations, and best-fit scenarios.

- Build end-to-end AI solutions, from data preprocessing to model deployment.

- Collaborate with product, engineering, and data teams to integrate AI features.

- Conduct POCs, research emerging GenAI technologies, and recommend adoption strategies.

- Ensure model performance, scalability, and responsible AI practices.

Required Skills & Qualifications

- 5 to 14 years of hands-on experience in GenAI and Machine Learning algorithms.

- Strong knowledge of Natural Language Processing (NLP) and large language models (LLMs).

- Proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and GenAI toolkits.

- Experience with LLM fine-tuning, prompt engineering, vector databases, and embeddings.

- Familiarity with AI/LLM platforms (OpenAI, AWS Bedrock, Azure OpenAI, HuggingFace, etc.).

- Ability to design, train, deploy, and monitor AI models.

- Strong problem-solving skills, creativity, and ability to work independently.

- Understanding of data engineering basics, APIs, and cloud environments (AWS/Azure/GCP).