Risk Modeling Solutions – Full-stack GenAI – Analyst II

Citi; Bengaluru; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

Citi is seeking a Full-Stack Gen AI Engineer in Bengaluru to design end-to-end AI workflows, orchestrate LLM pipelines, and build scalable Python microservices with FastAPI. You will implement RAG architectures and containerize services for Kubernetes deployments, while ensuring observability and robust testing.

Ideal candidates have 2+ years blending software development with data science, strong Python skills, and experience with LangChain/LangGraph, Docker, and cloud-based vector stores.

Qualifications

• 2 years of professional experience blending software development and data science.
• Strong Python development for AI systems and backend services.
• Experience building production APIs with FastAPI and microservices.
• Hands-on 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).
• Familiarity with Git-based workflows and collaborative development practices.
• A solid understanding of NLP fundamentals and Transformer architectures.

Responsibilities

• Develop end-to-end AI workflows focusing on reasoning, tool use, and memory.
• Build LLM orchestration pipelines with retrieval and memory layers.
• Develop Python-based microservices and REST APIs using FastAPI.
• Implement RAG pipelines with vector stores and embedding workflows.
• Containerize services with Docker and deploy on Kubernetes.
• Instrument workflows with observability platforms and maintain evaluation harnesses.
• Participate in code reviews and document engineering work.

Skills

Analytical Thinking

Credible Challenge

Data Analysis

Governance

Policy

Procedure

Regulation

Risk Management Lifecycle

Education

Bachelor’s degree in Computer Science, Engineering, Business, or a related field

Tools

Docker

Kubernetes

FastAPI

LangChain

LangGraph

CrewAI

LlamaIndex

OpenSearch

Pinecone

Chroma

Git

Job description

Full-Stack Gen AI Engineer – Model/Anlys/Valid Analyst II (C10)

Responsibilities

• AI Workflow Development: Implement end-to-end agentic AI workflows using frameworks like LangGraph, CrewAI, and AutoGen, focusing on reasoning, tool use, and memory.
• LLM Orchestration: Build and optimize retrieval pipelines, memory layers, and tool-use sequences using frameworks like LangChain.
• Backend & API Engineering: Develop robust, scalable Python-based microservices and REST APIs using FastAPI to expose AI capabilities.
• RAG Implementation: Construct and refine Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embedding, and vector search integration with databases like Azure AI Search or Pinecone.
• Containerization & Deployment: Package AI services using Docker and deploy them on Kubernetes, contributing to CI/CD pipelines for smooth and reliable releases.
• Observability & Evaluation: Instrument AI workflows using platforms like Langfuse for tracing and debugging. Implement and maintain evaluation harnesses to ensure model quality and performance.
• Engineering Excellence: Actively participate in code reviews, contribute to technical documentation, and collaborate with team members to uphold high engineering standards.

Qualifications

• 2 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.
• Experience 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).
• Familiarity with Git-based workflows and collaborative development practices.
• A solid understanding of NLP fundamentals and Transformer architectures.

Preferred Qualifications

• Experience 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.

Education: Bachelor’s degree in Computer Science, Engineering, Business, or a related field.

Job Family Group: Risk Management

Job Family: Model Development and Analytics

Time Type: Full time

Most Relevant Skills

• Analytical Thinking
• Credible Challenge
• Data Analysis
• Governance
• Policy
• Procedure
• Regulation
• Risk Management Lifecycle

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.