Main responsibilities:

As a Senior AI Engineer, you’ll be part of growing engineering team and help to build the next generation AI Solutions.

Collaborate with business stakeholders to understand use cases and define AI solution; work on Proof of Concepts wherever needed
Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD, etc.).
Build & maintain data pipelines and model performance for scalability and maintainability.
Ensure all models adhere to organizational AI policies, responsible AI practices, and audit requirements.
Support data exploration, feature engineering, and occasional model building where needed.
Automate model retraining, testing, and monitoring to ensure performance over time.
Document ML workflows, governance checkpoints, and risk assessments.
Partner with CloudOps,DevOps, IT, and security teams to integrate solutions into enterprise platforms.

Qualifications and Profile:

Have degree or master’s degree in the field of AI / ML and data science with proven ability to design and develop models
8+ years of experience in software development, data science and ML, with at least 3+ years in AI engineering roles.
Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
Strong programming skills in Python with Solid knowledge of AI/ML, including LLMs and data science libraries like pandas, scikit-learn, TensorFlow/PyTorch, etc.
Experience with LLM Orchestration frameworks like Langchain, LangGraph, vLLM, LMDeploy.
Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
Experience with MLOps tools: MLflow, Airflow, Kubeflow, or similar.
Familiarity with either of cloud platforms (GCP, AWS) for AI Solutioning and ML deployment.
Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.
Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
Strong understanding of AI governance, model risk management, and regulatory requirements in AI.
Ability to communicate technical concepts to non-technical stakeholders.

Preferred skills:

Experience with Responsible AI frameworks and bias/fairness testing.
Exposure to feature stores, model registries, and data versioning.
Knowledge of data privacy, anonymization, and compliance in regulated industries (e.g., banking, healthcare).

To Apply, please kindly email your updated resume to [email protected]

Regret to inform that only shortlisted candidates will be notified.

CEI: R25127749

EA License: 14C7275

Senior AI/ML Engineer (Banking Industry)