Generative AI Engineer

About the Role

We are looking for an AI Engineer with strong expertise in Generative AI, Large Language Models (LLMs), machine learning, and intelligent AI agents to develop AI-powered solutions for the Asset Liability Management (ALM) business. The role involves designing, developing, evaluating, and deploying AI applications that support financial analytics, risk modelling, and business decision-making. The ideal candidate will combine strong AI engineering capabilities with an interest in financial services, particularly lending, credit risk, and balance sheet optimization.

Key Responsibilities

• Generative AI & LLMs: Develop and fine-tune LLM-based applications, implement prompt engineering strategies, and optimize models for domain-specific financial use cases.
• AI Agents & Agentic Systems: Design and build autonomous AI agents, multi-agent architectures, and tool-calling workflows to automate complex analytical and business processes.
• ALM & Financial Analytics: Apply AI/ML techniques to Asset Liability Management use cases, including financial data analysis, risk assessment, scenario analysis, and decision-support systems.
• Lending & Credit Analytics: Develop AI-powered solutions for financial services use cases, including credit risk analysis, lending analytics, portfolio monitoring, and predictive modelling, as applicable.
• AI Evaluation & Optimization: Build evaluation frameworks and benchmarks to measure model accuracy, reliability, and performance, and continuously improve AI systems.
• Machine Learning & Deep Learning: Build, train, fine-tune, and evaluate ML and deep learning models for predictive analytics and business applications.
• Model Efficiency & Deployment: Optimize model inference, latency, memory usage, and computational costs using appropriate model optimization techniques.
• AI Application Development: Develop APIs and backend services to integrate AI models into production applications and analytical workflows.
• Cloud & Infrastructure: Build and deploy scalable AI solutions using cloud services and modern backend technologies.
• Research & Innovation: Evaluate emerging AI technologies and translate relevant research into practical solutions for financial services and ALM applications.
• Cross-functional Collaboration: Work with engineering, product, and business teams to translate financial and technical requirements into effective AI-powered solutions.

Requirements & Tech Stack

• Strong programming skills in Python and experience developing production-quality software.
• Hands-on experience with machine learning, deep learning, or Generative AI applications.
• Knowledge of LLMs, Transformers, model fine-tuning, prompt engineering, and model evaluation.
• Familiarity with AI agents, tool-calling systems, or multi-agent workflows.
• Experience with frameworks such as PyTorch, TensorFlow, or Hugging Face libraries.
• Strong analytical, mathematical, and problem-solving skills.
• Ability to develop APIs and integrate AI capabilities into software applications.
• Interest in applying AI to financial analytics, risk modelling, and business decision-making.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
• Preferred: Financial Services Experience (NBFCs, lending, credit risk, banking, or financial services).
• Preferred: Familiarity with Asset Liability Management, balance sheet analytics, financial risk modelling, or portfolio analysis.
• Preferred: Graduates from IITs or BITS campuses.
• Preferred: Candidates who graduated in 2025 or earlier.
• Preferred: Experience with AWS services such as Lambda, S3, DynamoDB, SQS, or SNS.
• Preferred: Exposure to RAG, embeddings, vector databases, AI evaluation frameworks, and production deployment.
• Preferred: Familiarity with model quantization, pruning, ONNX, and inference acceleration.
• Preferred: Publications, patents, or demonstrated contributions to applied AI projects.