We are looking for an experienced Data Scientist / Senior AI Engineer with 8-11 years of experience in building enterprise-scale AI, Machine Learning, Data Science, and Generative AI solutions. The ideal candidate should have strong hands-on expertise in Agentic AI, LLMs, multi-agent architectures, RAG, AI/ML model development, and AI-driven automation, along with strong software engineering and cloud capabilities.

Key Responsibilities:

- Design, develop, and deploy enterprise-scale AI/ML and Generative AI solutions for complex business use cases.

- Design and implement Agentic AI systems and multi-agent architectures using LLMs, tools, APIs, and orchestration frameworks.

- Build and optimize RAG pipelines, including document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.

- Develop and integrate LLM-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.

- Apply machine learning, deep learning, NLP, and statistical techniques to solve business problems.

- Develop AI-powered automation solutions using LLMs, intelligent agents, and workflow orchestration.

- Design and implement data pipelines required for AI/ML model development and deployment.

- Perform feature engineering, model development, evaluation, tuning, and performance optimization.

- Implement MLOps and LLMOps practices covering model/version management, deployment, monitoring, evaluation, and continuous improvement.

- Develop APIs and production-ready services to integrate AI solutions with enterprise applications.

- Implement responsible AI practices covering security, privacy, governance, monitoring, and model evaluation.

- Collaborate with Data Engineering, Software Engineering, Product, Cloud, and business teams to translate requirements into scalable AI solutions.

- Evaluate emerging AI technologies, models, frameworks, and tools and recommend their applicability to enterprise use cases.

- Mentor junior data scientists and AI engineers and provide technical guidance on AI architecture and implementation.

Required Skills:

- 8-11 years of experience in Data Science, AI/ML Engineering, Machine Learning, or related fields.

- Strong programming experience in Python and familiarity with software engineering best practices.

- Strong hands-on experience with Generative AI, LLMs, NLP, and Machine Learning.

- Proven experience building Agentic AI and multi-agent systems.

- Strong understanding of RAG architecture and LLM application development.

- Experience with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar.

- Experience working with OpenAI, Azure OpenAI, Anthropic, Gemini, or other commercial/open-source LLMs.

- Strong knowledge of prompt engineering, embeddings, vector databases, semantic search, and model evaluation.

- Experience with machine learning and deep learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.

- Strong SQL and data manipulation skills with experience working with structured and unstructured data.

- Experience with REST APIs, microservices, and cloud-based AI applications.

- Hands-on experience with AWS, Azure, or GCP.

- Experience with Docker, Kubernetes, CI/CD, and MLOps/LLMOps practices.

- Strong analytical, problem-solving, communication, and stakeholder-management skills.