Backend Engineer – LLM Integration (w/m/d) - Python, LangChain, LangGraph, or LiteLLM, Apache Kafka

Luxoft Germany; Ingolstadt; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

Luxoft Germany is seeking Backend Engineers to advance an in-vehicle AI voice assistant stack. You will build Python-based microservices, integrate LLM orchestration, and ensure robust real-time data handling with Kafka.

The role requires collaboration in a joint product team, deploying on AKS and contributing to architectural decisions. You will work with Docker/Kubernetes and maintain OpenAPI APIs, ADRs, and automated tests.

Qualifikationen

• 3+ years of 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.

Aufgaben

• Build and maintain FastAPI microservices that orchestrate LLM calls, tool use, and agentic workflows.
• 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 routing.
• Write unit, integration, and contract tests; maintain coverage and quality gates.
• Containerise services with Docker; deploy on AKS; contribute to Helm and Terraform configurations.
• Participate in code reviews with Audi engineers and contribute to architectural decisions.
• Monitor service health using Azure Monitor; triage and resolve production incidents.
• Document APIs (OpenAPI) and maintain ADRs for significant decisions.

Kenntnisse

Python development

FastAPI

LLM orchestration

Apache Kafka

English (B2)

Tools

Docker

Kubernetes

Terraform/Bicep (IaC)

Jobbeschreibung

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 Skills

• Terraform or Bicep for infrastructure-as-code
• Automotive domain or OEM project experience