We are seeking an experienced AI/ML Data Engineer to lead the development of AI-driven systems and scalable machine learning solutions.

The ideal candidate will have deep expertise in ML engineering, MLOps, and LLMOps, along with strong hands-on experience in cloud platforms and Python.

You will be responsible for designing, implementing, and optimizing pipelines that support advanced AI models, including LLM-based applications, RAG architectures, and fine-tuning workflows.

Key Responsibilities :

- Architect, build, and optimize AI/ML pipelines to support end-to-end machine learning and LLM workflows.

- Develop, maintain, and enhance LLM operations, including prompt engineering, fine-tuning, vector indexing, and Retrieval-Augmented Generation (RAG) implementations.

- Work with frameworks such as LangChain, LlamaIndex, Hugging Face models/tools, and similar orchestration frameworks to build scalable LLM-based solutions.

- Implement best practices in MLOps/LLMOps, including model deployment, monitoring, CI/CD automation, data versioning, and reproducibility.

- Design and deploy machine learning applications on Azure Cloud; experience with AWS or GCP is a strong plus.

- Collaborate with cross-functional teams including data scientists, product teams, and software engineers to translate business needs into robust AI solutions.

- Write production-grade Python code to support model training, evaluation, deployment, and automation.

- Perform data preprocessing, feature engineering, and integration of diverse data sources for AI systems.

- Ensure scalability, performance, and reliability of AI/ML workflows and deployed services.

- Continuously evaluate new tools, frameworks, and industry trends to enhance AI/ML ecosystem.

Required Skills & Qualification :

- 8+ years of professional experience in data engineering, AI/ML development, or related fields.

- 5+ years of hands-on experience in ML Engineering, MLOps, or LLMOps (mandatory).

- Strong understanding of LLM operations including prompt engineering, fine-tuning, embeddings, vector databases, and RAG pipelines.

- Hands-on experience in LangChain, LlamaIndex, Hugging Face, or similar AI orchestration frameworks.

- Proven ability to design, deploy, and manage ML workloads on Azure Cloud; AWS/GCP experience is an added advantage.

- 5+ years of experience in Python with strong coding, debugging, and automation skills.

- Solid understanding of machine learning lifecycle, model deployment best practices, monitoring, and CI/CD for ML systems.

- Good knowledge of data engineering workflows, data pipelines, and distributed processing environments.

- Strong problem-solving mindset with excellent communication and collaboration skills.

Additional Information :

- Locations available : Chennai, Bangalore, Pune.

- The role focuses on building advanced AI-driven systems, including generative AI and LLM-based solutions.

- Opportunity to work on cutting-edge AI technologies and scalable enterprise-grade ML platforms