At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
We are looking for a Senior Backend Engineer to design, develop, and scale high-performance backend services, integrating AI capabilities into modern distributed systems. This role combines strong backend engineering expertise with hands-on experience in LLM integrations, Retrieval-Augmented Generation (RAG), and tool calling, leveraging technologies such as Go, Python, and Microsoft Azure.
The ideal candidate will bring a solid understanding of microservices architecture, event-driven systems, distributed caching, and resilient service design to build reliable, scalable, and AI-enabled backend solutions.
- Backend Architecture & Development: Design, develop, and maintain scalable backend services and APIs using Go and Python, applying microservices and event-driven architecture principles to support high-performance, distributed applications.
- AI & LLM Integration: Integrate LLM capabilities into backend services, implementing RAG pipelines, tool calling, and AI orchestration patterns to enable intelligent, context-aware application workflows.
- Cloud Infrastructure & Performance Optimization: Build and integrate cloud-native services on Microsoft Azure, implementing distributed caching strategies with Redis and optimizing service performance, scalability, and resource utilization.
- Reliability & Distributed Systems Engineering: Design resilient backend architectures by implementing fault tolerance, retries, timeouts, and appropriate error-handling strategies, ensuring reliable communication and execution across distributed services and AI-powered workflows.
- Languages: Go (Golang) and Python.
- SAP integration (required): S/4HANA and ERP via OData, IDocs, BAPIs, RFCs, APIs and middleware. Preferred: BTP, CPI, MDG, Variant Configuration.
- Azure integration: APIM, Service Bus, Event Hubs, PostgreSQL, SQL, Entra ID, OAuth 2.0 and OIDC, Key Vault, networking, IaC.
- Caching (required): Redis, distributed caching, cache-aside, invalidation.
- AI (lighter): LLM integration, tool calling, RAG, and AI coding tools (Codex, Claude Code, Copilot).
- Architecture: microservices, event-driven systems, resiliency and retries.