Risk Modeling Solutions - Full-stack GenAI - Intermediate Analyst

Citi · Bengaluru · 4+ yrs experience · Posted 2026-07-18

Tech stack: AWS, Azure, Docker, FastAPI, GCP, Kubernetes, Python

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About the role

Full-Stack Gen AI Engineer – Model/Anlys/Valid Intmd Anlyst (C11) The AI Lab is the engineering core of our Risk Modeling Solutions (RMS) team, focused on integrating Gen AI solutions into our risk management framework. The team is responsible for building and deploying practical, high-impact applications that combine deep quantitative analysis with cutting-edge AI. These solutions enhance analytical decision-making, automate complex reporting, and create significant operational efficiencies for the business.
Responsibilities: - Full-Stack Gen AI Engineer
- Model/Anlys/Valid Intmd Anlyst (C11) The AI Lab is the engineering core of our Risk Modeling Solutions (RMS) team, focused on integrating Gen AI solutions into our risk management framework.
- The team is responsible for building and deploying practical, high-impact applications that combine deep quantitative analysis with cutting-edge AI.
- These solutions enhance analytical decision-making, automate complex reporting, and create significant operational efficiencies for the business.
Qualifications: - 4+ years of professional experience in a role blending software development and data science/machine learning.
- Strong Python development expertise for AI systems and backend services.
- building production APIs with FastAPI and microservices architecture.
- Proficiency with Docker and Kubernetes for containerized deployments.
- Hands-on experience with agentic AI or LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, LlamaIndex).
- Practical experience with RAG architecture, including vector databases (e.g., OpenSearch, Pinecone, Chroma).
- Proven ability to design and implement cost-effective AI architectures, with a deep understanding of tokenomics, model-tiering strategies, and caching for performance and budget management.
- Familiarity with Git-based workflows and collaborative development practices.
- A solid understanding of NLP fundamentals and Transformer architectures.
- with Langfuse or similar AI observability platforms.
- Hands-on use of a major cloud AI platform (AWS Bedrock, Azure AI Foundry, or GCP Vertex AI).
- Familiarity with enterprise data platforms like Snowflake or Redshift.
- Background in financial services or another regulated enterprise environment.
- Bachelor's degree in Computer Science, Engineering, Business, or a related field.

Qualifications

- 4+ years of professional experience in a role blending software development and data science/machine learning.
- Strong Python development expertise for AI systems and backend services.
- building production APIs with FastAPI and microservices architecture.
- Proficiency with Docker and Kubernetes for containerized deployments.
- Hands-on experience with agentic AI or LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, LlamaIndex).
- Practical experience with RAG architecture, including vector databases (e.g., OpenSearch, Pinecone, Chroma).
- Proven ability to design and implement cost-effective AI architectures, with a deep understanding of tokenomics, model-tiering strategies, and caching for performance and budget management.
- Familiarity with Git-based workflows and collaborative development practices.
- A solid understanding of NLP fundamentals and Transformer architectures.
- with Langfuse or similar AI observability platforms.
- Hands-on use of a major cloud AI platform (AWS Bedrock, Azure AI Foundry, or GCP Vertex AI).
- Familiarity with enterprise data platforms like Snowflake or Redshift.
- Background in financial services or another regulated enterprise environment.
- Bachelor's degree in Computer Science, Engineering, Business, or a related field.

Responsibilities

- Full-Stack Gen AI Engineer
- Model/Anlys/Valid Intmd Anlyst (C11) The AI Lab is the engineering core of our Risk Modeling Solutions (RMS) team, focused on integrating Gen AI solutions into our risk management framework.
- The team is responsible for building and deploying practical, high-impact applications that combine deep quantitative analysis with cutting-edge AI.
- These solutions enhance analytical decision-making, automate complex reporting, and create significant operational efficiencies for the business.

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