Job Description: AI Architect cum Data Scientist (LLM & Applied AI)

• Design and architect enterprise-scale AI/ML and Generative AI solutions.
• Build, train, fine-tune, and optimize Large Language Models (LLMs) for domain-specific applications.
• Make architectural decisions around:

• Model selection
• Data generation strategies
• Training pipelines
• Data governance and usage
• Retrieval-Augmented Generation (RAG)
• Prompt engineering frameworks

• Develop and deploy production-ready AI applications using LLMs and modern ML frameworks.
• Work hands-on with structured and unstructured data for analytics, feature engineering, and model development.
• Lead end-to-end ML lifecycle activities including experimentation, evaluation, deployment, monitoring, and optimization.
• Collaborate with engineering, product, and business teams to translate complex requirements into scalable AI solutions.
• Implement best practices for AI scalability, performance, observability, and responsible AI usage.
• Evaluate open-source and commercial LLM ecosystems and recommend optimal solutions.
• Mentor teams on AI/ML architecture, data science methodologies, and MLOps best practices.

We are seeking a highly experienced AI Architect cum Data Scientist with strong expertise in Generative AI, Large Language Models (LLMs), Machine Learning, and Advanced Analytics. The ideal candidate will have hands-on experience designing, training, fine-tuning, and deploying production-grade AI/LLM solutions for complex enterprise use cases., * 10+ years of experience in Data Science, AI/ML, or Advanced Analytics.

• Strong hands-on expertise in:

• Machine Learning
• Deep Learning
• Predictive Analytics
• Statistical Modeling
• NLP

• Proven experience with:

• LLM fine-tuning
• Model training
• Synthetic data generation
• Embedding models
• RAG architectures
• Vector databases

• Demonstrated success taking LLM-based complex use cases into production environments.
• Strong understanding of AI data pipelines, model evaluation, and governance.

Technical Skills

• Python, SQL, PySpark
• TensorFlow / PyTorch
• Hugging Face Transformers
• LangChain / LlamaIndex
• OpenAI, Anthropic, or open-source LLM ecosystems
• Vector databases such as Pinecone, Weaviate, FAISS, ChromaDB
• Cloud platforms: AWS / Azure / Google Cloud Platform
• MLOps tools and CI/CD pipelines
• Docker, Kubernetes, * Experience architecting enterprise AI platforms.
• Experience with multi-agent AI systems.
• Knowledge of responsible AI, AI safety, and compliance frameworks.
• Strong communication and stakeholder management skills.
• Experience working in fast-paced product or consulting environments., * Experience with multimodal AI models.
• Exposure to reinforcement learning or RLHF.
• Experience optimizing inference performance and GPU utilization.
• Prior experience in enterprise AI transformation initiatives.