AI Engineering Lead -N

Key Responsibilities

• Define system architecture for multimodal document processing, OCR, LMMs, and data pipelines.
• Design modular, pluggable OCR evaluation platform (Tesseract, Textract, DocAI, GPT-Vision, LayoutLM, Donut, etc.).
• Architect preprocessing (OpenCV), post-processing, normalization, and document understanding layers.
• Lead design of routing engines, ensemble logic, and feedback fine-tuning loops.
• Oversee data lake, vector index, and metadata storage design.
• Guide cloud infrastructure (AWS/Azure/GCP) for scalable processing of millions of documents.
• Partner with leadership on roadmap, cost optimization, and vendor evaluations.

Qualifications

• 5+ years overall IT experience across Data Engineering, Data Science and Gen-AI. Of this atleast 1+ year experience with data engineering and 1+ year experience on Gen-AI in production environments.
• Gen-AI expertise : Should have designed and developed Gen-AI applications. This should include building and deploying Agentic solutions and development of MCPs or integration of the AI components with IT applications in a production environment. Production environment meaning having experience of live usage of AI solutions and the associated tuning/improvement, change management and evaluation. 
• Data engineering expertise: Working with databricks based solutions and exposure to Airflow preferred.
• Domain experience : Working with capital markets or wealth management industry employer/client preferred.

There are multiple openings for this role. Atleast some of the team members should bring the preferred Data engineering and domain experience.