Python Backend Development Talent with RAG and Agentic AI Experience

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Чем предстоит заниматься

Design the end-to-end architecture for a scalable RAG system and AI chatbot

Develop Python backend services, REST APIs, and microservices using FastAPI or similar frameworks

Build document ingestion, chunking, embedding, indexing, retrieval, and reranking pipelines

Implement vector search solutions using Azure AI Search or comparable vector databases

Design autonomous AI agents capable of planning, reasoning, tool usage, and decision-making

Develop multi-step AI workflows using LangGraph, LangChain, CrewAI, AutoGen, or similar orchestration frameworks

Integrate commercial and open-source LLMs, including Azure OpenAI, OpenAI, Anthropic Claude, Gemini, and comparable models

Implement conversation memory, session management, context management, and agent collaboration patterns

Connect AI workflows with APIs, databases, enterprise systems, and external tools

Develop asynchronous, high-performance services capable of handling concurrent AI workloads

Implement prompt management, structured outputs, guardrails, fallback logic, and model evaluation processes

Establish logging, monitoring, tracing, observability, security, and error-handling standards

Containerize and deploy AI services using Docker, Kubernetes, Azure, or AWS

Translate business requirements into technical designs, delivery milestones, and production-ready AI solutions

Collaborate with the wider team while independently owning architecture and implementation decisions

Наши требования

The organization is developing an AI-powered platform and requires an experienced individual contributor to build its RAG architecture and conversational AI capabilities. The developer will work closely with a distributed team and should be available for several hours of overlap with US working hours

The project involves designing AI systems that go beyond basic prompt engineering, including multi-step workflows, autonomous agents, vector search, knowledge retrieval, memory management, and tool integration. The solution must be scalable, secure, observable, and suitable for production use

The technology environment includes Python, FastAPI, large language models, LangGraph, LangChain, vector databases, Azure AI services, AWS, Docker, Kubernetes, and microservice-based architectures

Required: 8 or more years of professional Python backend development experience

Required: Strong experience designing REST APIs, microservices, asynchronous services, and distributed backend systems

Required: Hands-on experience building production-grade RAG applications

Required: Strong understanding of embeddings, document chunking, semantic search, vector indexing, retrieval strategies, and reranking

Required: Hands-on experience developing AI agents and multi-step LLM workflows

Required: Experience with agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or comparable platforms

Required: Experience integrating LLMs through OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or open-source model APIs

Required: Ability to design AI architecture beyond basic prompt engineering

Required: Experience integrating AI applications with APIs, databases, data pipelines, and enterprise systems

Required: Experience implementing security, monitoring, logging, tracing, and observability for production services

Required: Experience deploying containerized applications using Docker and cloud platforms such as Azure or AWS

Required: Ability to independently translate business requirements into scalable technical solutions

Required: Strong communication and collaboration skills in a distributed working environment

Required: Availability for several hours of overlap with US working hours

Дополнительно

We are seeking an experienced Python Backend Developer to design, build, and deploy scalable AI-powered applications using Retrieval-Augmented Generation, large language models, and agentic AI frameworks. The role will focus on delivering a production-grade RAG system and AI chatbot that can securely integrate with enterprise data, APIs, databases, and cloud services

Toptal

Asia Only

ГрейдMiddle

ЗанятостьПолная занятость

РегионАзия

ФорматУдалённо

ИсточникСкрыто

Опубликовано12 авг.

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