Risk Modeling Solutions - Full-stack GenAI - Analyst II

Jobtailor; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Jobtailor in Bengaluru, India seeks a skilled AI/ML backend engineer to design and implement end-to-end agentic AI workflows. You will build scalable Python microservices and REST APIs with FastAPI, and deploy via Docker and Kubernetes.

Experience with LangChain, LangGraph, and RAG architectures is essential to orchestrate LLM workflows and vector stores. You will collaborate on retrieval pipelines, memory layers, and tool-use sequences, while maintaining robust documentation and engineering

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.

Responsibilities

• Implement end-to-end agentic AI workflows using LangGraph, CrewAI, and AutoGen.
• Build and optimize retrieval pipelines, memory layers, and tool-use sequences using LangChain.
• Develop robust, scalable Python-based microservices and REST APIs using FastAPI.
• Construct and refine Retrieval-Augmented Generation (RAG) pipelines.
• Package AI services using Docker and deploy them on Kubernetes.
• Instrument AI workflows using Langfuse for tracing and debugging.
• Contribute to technical documentation and uphold high engineering standards.

Skills

Python

FastAPI

Docker

Kubernetes

LangChain

LangGraph

CrewAI

LlamaIndex

RAG

OpenSearch

Pinecone

Chroma

Git

NLP fundamentals

Transformer architectures

Tools

FastAPI

Docker

Kubernetes

LangChain

LangGraph

CrewAI

LlamaIndex

OpenSearch

Pinecone

Chroma

Job description

Responsibilities

• Implement end-to-end agentic AI workflows using frameworks like LangGraph, CrewAI, and AutoGen.
• Build and optimize retrieval pipelines, memory layers, and tool‑use sequences using frameworks like LangChain.
• Develop robust, scalable Python‑based microservices and REST APIs using FastAPI.
• Construct and refine Retrieval‑Augmented Generation (RAG) pipelines.
• Package AI services using Docker and deploy them on Kubernetes.
• Instrument AI workflows using platforms like Langfuse for tracing and debugging.
• Contribute to technical documentation and uphold high engineering standards.

Requirements

• 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.

Core Competencies

Demonstrates expertise in developing and optimizing AI workflows, microservices, and APIs, with a strong focus on Python, containerization, and retrieval‑augmented generation techniques. Proficient in utilizing frameworks and tools for building scalable AI systems and ensuring high engineering standards.