Senior AI Engineer

Key Responsibilities:

• Own the end-to-end lifecycle of AI features from requirement understanding and solution design to development, deployment, and monitoring.
• Build LLM/RAG-based solutions using vector databases (e.g., pgvector, FAISS, Chroma, OpenSearch) for search, QA, extraction, and summarization over documents.
• Develop Document AI models/pipelines for OCR post-processing, entity/key-value extraction, classification, and layout/table understanding.
• Deploy models as scalable APIs/microservices in cloud and on-prem environments using Python, Docker, and CI/CD.
• Work directly with client stakeholders to refine requirements, present solutions, and handle reviews/clarifications.
• Act as technical lead on 2- 3 AI projects, guiding the team on architecture, design, and best practices.
• Mentor junior AI engineers via code reviews, design discussions, and technical coaching.
• Design with security, privacy, and cost in mind, especially for data-sensitive domains (BFSI, healthcare, legal, HR)

Must-Have Experience Requirements:

• 4-6 years total experience, including 3+ years in AI/DL/NLP in production environments.
• Proven experience taking AI solutions from PoC to production (not just notebooks).
• Strong in Python and core CS fundamentals (data structures, algorithms, clean code).
• Hands-on with AI/NLP/LLMs classification, NER, QA, summarization, document understanding.
• Experience with some of: PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, spaCy.
• Built and deployed RESTful ML services/APIs integrated with web or mobile applications.
• Worked with Docker and CI/CD pipelines; experience with AWS or GCP.
• Good SQL skills and experience with at least one RDBMS (PostgreSQL/MySQL).
• Understanding of MLOps in production monitoring, logging, model versioning, rollback, performance & cost optimization.