Role & 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, CA, 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 23 AI projects, guide 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

Preferred candidate profile :

Technical Skills

- Robust in Python and core CS fundamentals (data structures, algorithms, clean code).
- Hands-on with AI / NLP / LLMs classification, NER, A, 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 of AWS or GCP. Good SQL skills and experience with at least one RDBMS (PostgreSL/MySL).
- Understanding of MLOps in production monitoring, logging, model versioning, rollback, performance C cost optimisation. Soft Skills
- Comfortable interacting with international clients and leading requirement / review calls.
- Strong ownership mindset and ability to lead and mentor junior engineers.

Good-to-Have

- Experience in Logistics, Legal, HR/Recruitment, Healthcare, BFSI, Education, Engineering/Plant drawings.
- Exposure to Vision Transformers / advanced CV for document layout and OCR enhancement.
- Experience with experiment tracking tools (MLflow, DVC, WCB, etc.). Exposure to security G compliance (CIS, SOC2, GDPR, HIPAA, PCI-DSS, ITIL).
- Experience with on-prem / VPC-isolated deployments and data-sensitive environments.
- Knowledge of a systems language (Go / Rust / C++ / Scala) is a plus, not mandatory.
- 5 - 12 years of experience preferred.

Contact No ; (phone hidden)

📌 Senior/Lead AI Engineer (Chennai)
🏢 Modinity Technologies
📍 Chennai