Senior AI Engineer - (AI, ML, Data Scientist)

Job Summary

We are seeking a Senior AI Engineer to join a growing engineering team to design, build, and deliver next-generation AI solutions for enterprise projects in banking industry. In this role, you will collaborate with business stakeholders, data teams, and platform engineering groups to develop scalable, secure, and responsible AI systems.

Mandatory Skill-set

• Bachelor's or Master's degree in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or a related field;
• Must have 8+ years of experience in software development, data science, or ML engineering,
• Must have 3+ years in dedicated AI engineering roles;
• Proven experience across the full ML lifecycle: data processing, model development, deployment, monitoring, and optimization;
• Must have experience in Python and widely used AI/ML frameworks such as pandas, scikit-learn, TensorFlow, PyTorch, and others;
• Hands-on experience working with Large Language Models (LLMs) and orchestration frameworks such as LangChain, LangGraph, vLLM, or LMDeploy;
• Solid understanding of NoSQL databases;
• Experience with MLOps platforms such as MLflow, Airflow, Kubeflow, or similar;
• Familiarity with modern cloud platforms (GCP or AWS) for AI development and deployment;
• Knowledge of supervised/unsupervised learning, NLP, time-series modeling, and related data science techniques;
• Experience with CI/CD, Docker, and Kubernetes;
• Strong understanding of AI governance, model risk management, and related regulatory frameworks.

Desired Skill-set

• Experience with Responsible AI frameworks, fairness/bias assessment, and model explainability tools;
• Exposure to graph databases;
• Exposure to feature stores, model registries, and data/version management tools;
• Understanding of data privacy, anonymization, and compliance requirements in regulated industries.

Responsibilities

• Collaborate with business stakeholders to understand use cases, define AI solution approaches, and build Proofs of Concept (PoCs) when required;
• Engineer, deploy, and maintain machine learning models in production using best-in-class MLOps practices (model versioning, CI/CD, observability, monitoring and others;
• Build and maintain scalable, maintainable data pipelines and monitor model performance across environments;
• Ensure all AI solutions comply with organizational AI policies, responsible AI guidelines, and audit/regulatory requirements;
• Support data exploration, feature engineering, and hands-on model development when necessary.
• Automate model retraining, testing, evaluation, and performance monitoring workflows;
• Document ML workflows, governance controls, and model risk assessments;
• Partner with CloudOps, DevOps, IT, and Security teams to successfully integrate AI solutions into enterprise platforms;
• Contribute to continuous improvement of engineering standards, automation, and reusable AI components.

Should you be interested in this career opportunity, please send in your updated resume to [Confidential Information] at the earliest.

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