Manager- AI Automation

About the Role

Kotak Alternate Asset Management Limited (KAAML) is seeking a Full Stack AI Automation Engineer with strong expertise in AI/ML, financial services, and quantitative systems. The role involves designing, building, and optimizing AI-driven solutions that power next-generation financial products, AIF platforms, and risk management systems.

The ideal candidate combines deep knowledge of AI tools, AI frameworks, machine learning, NLP/LLMs, and generative AI with hands-on experience in Python, React.js, and AWS cloud, along with strong domain understanding of banking, asset management, Alternate investment fund, trading, or fintech.

Key Responsibilities

AI / ML Model Development

• Design, build, train, and deploy AI/ML models for:
• Risk scoring
• Portfolio optimization
• Fraud detection
• Regulatory and compliance reporting
• Fund allocation and NAV calculations.
• Data warehouse
• Apply NLP and LLM techniques to analyse financial documents, contracts, and market reports.
• Experiment with Generative AI, Reinforcement Learning, and Explainable AI (XAI) to enhance decision-making.

LLMs, RAG & Vector Tools

• LangChain / LangGraph
• LlamaIndex
• Vector DBs: Pinecone / OpenSearch / pgvector / Weaviate
• Prompt engineering, structured output (Pydantic)
• N8n or other orchestration tools.

Model Deployment & MLOps

• Implement CI/CD pipelines for ML models with monitoring, logging, and drift detection.
• Deploy and manage models on AWS using services such as:
• SageMaker, EKS, Lambda
• Redshift, S3, Glue, Athena
• Ensure auditability, reproducibility, and compliance with SEBI and RBI regulations.

Engineering & Automation

• Develop scalable backend services using Python (Flask / FastAPI / Django).
• Build secure APIs using OAuth 2.0 and JWT for model access and system integration.
• Automate workflows such as login processes, document processing, and data uploads/downloads using Playwright.
• Develop React.js dashboards to deliver interactive AI-driven insights related to risk, portfolio performance, and compliance.

Performance, Security & Compliance

• Optimize AI/ML pipelines for low latency and high throughput.
• Implement secure coding practices, including token storage, CSRF protection, and data governance.
• Collaborate closely with risk, compliance, and audit teams to ensure regulatory alignment of AI systems.

Required Skills

• AI / ML: Supervised & unsupervised learning, NLP/LLMs, generative AI, time-series forecasting.
• Programming: Python (Flask, Django, FastAPI), React.js.