Risk Modeling Solutions - Full-stack GenAI - Assistant Vice President

Citibank (Switzerland) AG; Bengaluru; Hybrid; Confidential; Full time

Job summary

Citibank (Switzerland) AG is recruiting a Risk Modeling Solutions GenAI Lead Engineer in a hybrid setup across Bengaluru and Mumbai. You will design complex agentic AI workflows, translate risk problems into robust AI solutions, and build end-to-end pipelines with multi-frameworks while ensuring governance and safety.

Ideal candidates have 6+ years in software/data science roles, expert Python, FastAPI, and hands-on experience with LangChain, LangGraph, and Docker/Kubernetes in cloud

Qualifications

• 6+ years blending software development and data science/ML.
• Expert Python and scalable backend/API design (FastAPI preferred).
• Experience with multiple agentic frameworks (LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel).
• RAG systems design and integration with vector databases (OpenSearch, Pinecone, Weaviate).
• Containerized AI systems on Docker/Kubernetes across cloud platforms (AWS/Azure/GCP).
• CI/CD, observability, evaluation for LLM-based systems (MLOps).
• Knowledge of AI risk, safety, governance.

Responsibilities

• Architect agentic AI workflows capable of reasoning, planning, and autonomous execution.
• Translate business problems into robust technical requirements and end-to-end AI solutions.
• Develop end-to-end AI workflows with LangGraph, CrewAI, AutoGen, including memory and tool-use.
• Build LLM orchestration and retrieval pipelines using LangChain.
• Develop Python-based microservices and REST APIs with FastAPI.
• Contribute to CI/CD and deployment on Kubernetes; ensure observability with Langfuse.
• Evaluate model quality with harnesses and governance considerations.

Skills

Python

FastAPI

Agent frameworks

RAG systems

Vector databases

Docker/Kubernetes

MLOps

LLM safety

Cloud platforms

NLP/Transformers

Tools

OpenSearch

Pinecone

Weaviate

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Docker

Kubernetes

AWS

Azure

GCP

Job description

## Risk Modeling Solutions - Full-stack GenAI - Assistant Vice PresidentApply: Hybrid: Bangalore Karnataka India: Mumbai Maharashtra India: Full time: Posted Today: End Date: September 22, 2026 (6 days left to apply): 26985465**Risk Modeling Solutions - Gen AI Lead Engineer****Description:**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.**The responsibility includes but not limited to the following activities:*** **Architect Agentic Systems:** Design and lead the implementation of complex, multi-agent AI workflows capable of advanced reasoning, planning, and autonomous execution using frameworks like LangGraph, CrewAI, and Google ADK.* **Solution Design & Development:** Translate complex business problems within the risk domain into well-defined technical requirements, and develop robust, end-to-end AI solutions to address them.* **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.**Qualifications:*** 6+ years of professional experience in a role blending software development and data science/machine learning.* Expert-level Python development skills and a proven track record of designing and building scalable backend services and APIs (FastAPI preferred).* Deep, hands-on experience designing and building solutions with multiple agentic frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel).* Extensive experience architecting and optimizing RAG systems and integrating with vector databases (e.g., OpenSearch, Pinecone, Weaviate).* Proven expertise in designing and deploying containerized (Docker/Kubernetes) AI systems on a major cloud platform (AWS, Azure, or GCP).* Strong experience implementing MLOps principles, including CI/CD, observability, and evaluation frameworks for LLM-based systems.* In-depth understanding of AI risk, safety, and enterprise governance requirements.* Strong background in ML, deep learning, and NLP, including Transformer architectures.**Preferred Qualifications*** Experience leading the design of LLM evaluation harnesses for automated release validation.* Deep experience with Langfuse or similar AI observability and tracing platforms.* Hands-on expertise with AWS Bedrock, Azure AI Foundry, or GCP Vertex AI.* Knowledge of GraphRAG patterns and advanced multi-hop retrieval strategies.* AWS certifications (e.g., Solutions Architect, AI/ML Specialty) or equivalent.* Background in financial services or another highly regulated industry.