Job Description

AI/ML Engineer (Agentic AI & Data Science)

About the Role

We are seeking an AI/ML Engineer with Data Science and GenerativeAI capabilities to design and deliver next-generation AI solutions across Global Financial Markets.

The role will focus on developing Agentic AI platforms, recommendation engines, retrieval systems, and predictive models supporting initiatives such as market intelligence, product recommendations, client engagement, workflow automation, and knowledge management.

You will work closely with business stakeholders, product owners, data scientists, and software engineers to translate business challenges into scalable AI-powered solutions.

Key Responsibilities

Generative AI & Agentic AI

Design and develop AI agents using modern agent frameworks.
Build and optimize RAG (Retrieval-Augmented Generation) solutions.
Develop agent orchestration workflows and tool-calling frameworks.
Implement prompt engineering, evaluation, reflection, and memory capabilities.
Build reusable AI components that can be leveraged across multiple business use cases.

Machine Learning & Data Science

Develop machine learning models for:
Client propensity prediction
Recommendation systems
Classification and ranking
Behavioral analytics
Next-best-action recommendations
Perform data exploration, feature engineering, and model evaluation.
Analyze large structured and unstructured datasets to generate actionable insights.
Monitor model performance and continuously improve accuracy and relevance.

AI Application Development

Build production-ready AI services and APIs.
Integrate AI solutions with enterprise systems and data sources.
Implement monitoring, observability, and evaluation frameworks.
Optimize AI solutions for performance, scalability, and cost efficiency.

Required Qualifications

Experience:

Machine Learning Engineering
Data Science
AI Engineering
Advanced Analytics
Hands-on experience building and deploying ML or AI solutions into production.

Technical Skills

Programming

Python (mandatory)
SQL
REST APIs

Machine Learning

Experience with:

Scikit-Learn
XGBoost/ LightGBM
TensorFlow or PyTorch

Generative AI - (MANDATORY)

Experience in all the following areas:

RAG
Vector Search
LLM Applications
Dify
Agentic AI frameworks

Data Engineering

Knowledge of:

Data pipelines
Data transformation
Feature engineering
Data quality management

Cloud & DevOps

Experience with:

OCP (Openshift Platform)
Docker
Kubernetes
CI/CD pipelines
Git

Preferred Qualifications

Experience with financial services, banking, capital markets, or wealth management.
Experience building recommendation engines or personalization solutions.
Experience with search, retrieval, and knowledge management platforms.
Familiarity with MLOps, LLMOps, and AI governance practices.
Experience working with unstructured document repositories and enterprise knowledge sources.