Location: PAN India / Hybrid
Experience: 5 15 Years (Based on Level)
Employment Type: Full-Time
Domain: BFSI (Banking, Financial Services Insurance) Cards Payments
Skills: GenAI, LLMOps, Data Science, Machine Learning, MLOps, NLP, Python, Cloud Platforms

About the Role

We are looking for highly skilled GenAI, LLMOps, and Data Science professionals with solid BFSI and Cards domain expertise to build next-generation AI-driven solutions for banking and financial services. The ideal candidate will work on Large Language Models (LLMs), Generative AI applications, intelligent automation, fraud analytics, customer intelligence, risk modeling, and payment/card-related use cases.

The role involves designing, developing, deploying, and monitoring enterprise-scale AI/ML solutions while ensuring compliance, governance, scalability, and performance in a regulated financial environment.

Key Responsibilities Generative AI LLM Solutions

- Design, develop, and deploy GenAI applications using Large Language Models.
- Build RAG (Retrieval Augmented Generation) based solutions for enterprise knowledge management.
- Fine-tune and optimize open-source and commercial LLMs for BFSI-specific use cases.
- Develop conversational AI, virtual assistants, document intelligence, and financial advisory solutions.
- Implement prompt engineering, evaluation frameworks, guardrails, and responsible AI practices.

LLMOps MLOps
- Build scalable LLMOps pipelines for model deployment, monitoring, governance, and lifecycle management.
- Implement CI/CD pipelines for AI/ML models.
- Establish model observability, drift detection, performance tracking,



and retraining strategies.
- Manage vector databases, embeddings, model registries, and inference platforms.
- Ensure compliance with enterprise security and regulatory requirements.

Data Science Advanced Analytics
- Develop predictive, classification, recommendation, and anomaly detection models.
- Build fraud detection, credit risk, customer segmentation, churn prediction, and transaction analytics solutions.
- Perform feature engineering, model validation, and explainability analysis.
- Leverage structured and unstructured financial data for business insights.

BFSI Cards Domain
- Work on card lifecycle management, payment processing, authorization, settlements, chargebacks, disputes, and fraud analytics.
- Develop AI-driven solutions for card portfolio optimization and customer engagement.
- Understand regulatory and compliance requirements applicable to banking and payments.
- Collaborate with business stakeholders to identify AI opportunities across Cards and Payments ecosystems.

Stakeholder Management
- Collaborate with business, product, engineering, and architecture teams.
- Translate business requirements into scalable AI and analytics solutions.
- Mentor junior team members and contribute to AI best practices.

Required Skills Technical Skills




- Strong experience in Python, SQL, and Machine Learning.
- Hands-on experience with Generative AI frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar.
- Experience with OpenAI, Claude, Gemini, Llama, Mistral, or equivalent LLM platforms.
- Expertise in RAG architectures, Vector Databases, Embeddings, and Prompt Engineering.
- Experience with MLOps/LLMOps tools and frameworks.
- Knowledge of Docker, Kubernetes, CI/CD, and API development.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Strong understanding of NLP, Deep Learning, and AI model evaluation.

Domain Skills
- Strong BFSI experience.
- Hands-on exposure to Cards Payments domain.
- Knowledge of Fraud, Risk, AML, Customer Analytics, or Credit Analytics is highly preferred.

Preferred Qualifications
- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, AI/ML, or related field.
- Certifications in GenAI, Machine Learning, Cloud Platforms, or Data Science.
- Experience working in enterprise-scale BFSI environments.
- Exposure to Responsible AI, AI Governance, and Regulatory Compliance.

Experience Compensation

Level Experience Budget Range L3 5 8 Years 25 32 LPA (including 5% fixed variable) L4 8 10 Years 35 45 LPA (including 5% fixed variable) L5 12 15 Years 50 60 LPA (including 15% VP component)

Mandatory Skills

- Generative AI
- LLMOps / MLOps
- Data Science
- Python
- Machine Learning
- NLP
- BFSI Domain
- Cards Payments
- RAG
- Prompt Engineering
- Vector Databases
- AWS / Azure / GCP

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