AI Software Engineer (Agentic Workflows, Production Systems)

United States Digital Space LLC; Barra do Garças; Presencial; BRL 180 000 - 300 000; Tempo integral

Resumo da oferta

United States Digital Space LLC seeks an experienced AI Engineer to design and deploy agentic AI workflows, focusing on RAG pipelines, vector databases, Embeddings, and efficient model orchestration. You will develop scalable Python/Java services and integrate AI components into enterprise CI/CD environments.

Applicants should excel in prompt engineering, context-window optimization, and production-grade implementations, collaborating with cross-functional teams to deliver secure, cost-effective

Qualificações

• Hands-on experience designing and deploying production-grade agentic AI workflows.
• Strong Python development experience; Java is desirable.
• Deep expertise with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and hybrid search.
• Experience with LangGraph, LangChain, MCP, FastAPI, and asynchronous Python development.
• Strong understanding of prompt engineering, context window optimization, and LLM orchestration patterns.
• Experience implementing AI solutions within enterprise CI/CD pipelines and production environments.

Responsabilidades

• Design and implement production-ready agentic AI workflows.
• Build, optimize, and maintain RAG pipelines with vector databases and prompt optimization.
• Develop scalable Python and Java services following enterprise software engineering practices.
• Integrate AI services into CI/CD pipelines with monitoring and observability.
• Design prompt strategies to optimize context windows and costs.
• Implement evaluation frameworks, hallucination detection, guardrails, and feedback loops.
• Collaborate with cross-functional teams to deliver secure, scalable AI solutions.

Conhecimentos

Agentic AI workflows

Python development

RAG pipelines

vector databases

LangGraph/LangChain

MCP/FastAPI

Context window optimization

LLM orchestration

CI/CD in production

Ferramentas

LangGraph

LangChain

Model Context Protocol

FastAPI

Descrição da oferta de emprego

Why Join the company

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client

A preeminent professional services network and one of the world's leading accounting firms. The organization delivers industry-leading assurance, advisory, and tax services to top-tier global enterprises. Today, the firm integrates robust cloud systems and scalable generative AI to solve complex digital challenges and deliver advanced automation tools worldwide.

What You’ll Do

• Design and implement production-ready agentic AI workflows using modern multi-agent and single-agent architectures.
• Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases, hybrid search, retrieval re-ranking, and prompt optimization.
• Develop scalable Python and Java services following enterprise software engineering best practices.
• Integrate AI services into CI/CD pipelines while implementing monitoring, logging, and observability for production environments.
• Design prompt engineering strategies that optimize context windows, model performance, and operational costs.
• Implement evaluation frameworks, hallucination detection, guardrails, and continuous feedback loops to improve model quality and reliability.
• Collaborate with cross-functional engineering teams to deliver secure, scalable AI solutions that solve complex business problems.

What You Bring

• Hands‑on experience designing and deploying production‑grade agentic AI workflows.
• Strong Python development experience; Java experience is highly desirable.
• Deep expertise with Retrieval‑Augmented Generation (RAG), vector databases, embeddings, hybrid search, and retrieval optimization.
• Experience with LangGraph, LangChain, Model Context Protocol (MCP), FastAPI, and asynchronous Python development.
• Strong understanding of prompt engineering, context window optimization, and LLM orchestration patterns.
• Experience implementing AI solutions within enterprise CI/CD pipelines and production environments.