Backend Engineer – LLM Integration

Luxoft; Ingolstadt; Vor Ort; EUR 70.000 - 110.000; Vollzeit

Zusammenfassung

Luxoft in Ingolstadt, Germany is seeking a Backend Engineer to advance AI-driven, in-vehicle voice assistant integration. You will build, test, and operate FastAPI microservices that connect AI/ML components with vehicle-cloud communication pipelines on AKS, using LangChain/LiteLLM and Kafka.

You will collaborate in a joint product team with Azure OpenAI integration, manage prompt routing, and ensure production readiness through tests and observability, while contributing to architectural

Qualifikationen

• 3+ years of professional Python development with production web services.
• Experience with FastAPI (or Flask/Django) for REST APIs.
• Familiarity with at least one LLM orchestration framework: LangChain, LangGraph, or LiteLLM.
• Apache Kafka producer/consumer and understanding of delivery semantics.
• Docker and Kubernetes basics (deployment manifests, service configuration).
• English at least B2 (B2 or above).

Aufgaben

• Build and maintain FastAPI microservices that orchestrate LLM calls, tool use, and agentic workflows.
• Integrate with Azure OpenAI endpoints and manage prompt versioning and routing.
• Write unit and integration tests (pytest) and maintain quality gates in CI/CD.
• Containerise services with Docker; deploy on AKS; contribute to Helm charts and Terraform.
• Participate in code reviews with Audi engineers and contribute to joint architectural decisions.
• Monitor service health using monitoring tools and triage incidents.
• Document APIs (OpenAPI) and maintain ADR entries.

Kenntnisse

Python

FastAPI

LangChain / LangGraph / LiteLLM

Apache Kafka

Docker

Kubernetes

English (B2)

Tools

AKS

Azure OpenAI

Jobbeschreibung

Project description

Our client is advancing its in-vehicle voice assistant into an intelligent, AI-powered companion. Since 2024, they have been incorporating large-language-model capabilities (Azure OpenAI / ChatGPT) into vehicles equipped with the MIB3 infotainment system, with new E³-architecture models featuring enhanced voice functions from the factory. The AIME (AI Model Engine) backend program supports this development over a multi-year timeline, addressing natural-language dialogue, empathic communication, and the complete cloud-edge data pipeline. DXC Luxoft serves as the end-to-end delivery partner, collaborating closely with the client's engineers within a joint product team on the Azure platform (AKS, Azure OpenAI, Managed Identity, Azure Monitor, Azure DevOps).

Responsibilities

• Backend Engineers in this stream own the integration layer between the AI/ML components and the vehicle/cloud communication backbone. The stack is Python-first, event-driven via Kafka, and exposed through FastAPI services running on AKS. You will work inside the joint product team, picking up S/M/L backlog tickets and shipping production-ready code.
• Build and maintain FastAPI microservices that orchestrate LLM calls, tool use, and agentic workflows using LangChain / LangGraph.
• Implement Kafka producers and consumers for real-time voice session data, telemetry, and event-driven AI triggers.
• Integrate with Azure OpenAI endpoints via LiteLLM abstraction; manage prompt versioning and A/B routing.
• Write unit, integration, and contract tests (pytest, Pact); maintain coverage and quality gates in Azure DevOps.
• Containerise services with Docker; deploy and operate on AKS; contribute to Helm chart and Terraform configuration.
• Participate in code reviews with Audi engineers and contribute to joint architectural decisions.
• Monitor service health using Azure Monitor / Application Insights; triage and resolve production incidents.
• Document APIs (OpenAPI) and maintain ADR entries for significant implementation decisions.

SKILLS

Must have

• 3+ years professional Python development, including production web services.
• Experience with FastAPI (or Flask/Django) for REST API design.
• Familiarity with at least one LLM orchestration framework: LangChain, LangGraph, or LiteLLM.
• Apache Kafka - producer/consumer implementation; at-least-once vs exactly-once semantics.
• Docker and Kubernetes basics (deployment manifests, service configuration).
• English B2 or above.

Nice to have

• Azure services: AKS, Azure OpenAI, Managed Identity, CosmosDB.
• Terraform or Bicep for infrastructure-as-code.
• Automotive domain or OEM project experience.
• Async Python patterns (asyncio, aiohttp).
• German language skills.