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Tier-1 brand, metro Bangalore location, and mid-level generalist GenAI role increase competition.
GenAI and backend engineering skills are transferable across industries, though regulated finance experience is beneficial.
Explicit 2+ years plus mandatory FastAPI, Docker, Kubernetes, and LLM orchestration requirements raise screening strictness.
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Develop and deploy end-to-end agentic AI workflows and LLM orchestration pipelines using frameworks like LangGraph and LangChain to enhance risk management applications.
Build scalable Python microservices and REST APIs with FastAPI to expose AI capabilities, including implementing Retrieval-Augmented Generation (RAG) pipelines with vector databases.
Package AI services with Docker, deploy on Kubernetes, and maintain observability and evaluation tooling to ensure AI model quality and operational reliability.
Minimum 2+ years of professional experience combining software development and data science/machine learning.
Strong Python development skills with experience in backend services and building production APIs using FastAPI and microservices architecture.
Hands-on experience with containerization and orchestration tools: Docker and Kubernetes.
Bachelor's degree in Computer Science, Engineering, Business, or related field.
Experience working with agentic AI or large language model orchestration frameworks (e.g., LangChain, LangGraph, CrewAI).
Proficiency in implementing RAG architectures and integrating vector databases (e.g., Pinecone, OpenSearch).
Background or familiarity with financial services or regulated enterprise environments preferred but not mandatory.