Technical Lead Backend – AIME Platform

Luxoft Germany; United States; Hybrid; USD 150,000 - 190,000; Full time

Job summary

Luxoft Germany seeks a Technical Lead and Location Lead for a backend AI orchestration platform serving in-vehicle voice assistant systems. You will steer the backend team, own architecture and production reliability, and deliver streaming AI services in a joint product team with client engineers on the Azure stack.

You will stay hands-on with critical components, drive code reviews, ensure quality gates, and collaborate across CET time zones.

Qualifications

• 8+ years of backend engineering with Python and leadership
• Hands-on Python (FastAPI, asyncio) and core implementation work
• Experience with streaming architectures in production
• REST/gRPC with OAuth2/mTLS for secure APIs
• PostgreSQL design, tuning, migrations with Alembic
• Experience integrating LLM APIs into production backends (Azure/OpenAI)
• Container orchestration with Docker/Kubernetes in production
• Azure cloud (AKS/Container Apps) and Terraform/IaC
• Monitoring, tracing (OpenTelemetry) and incident management
• CI/CD ownership on Azure DevOps and/or GitHub; automated tests
• Scrum processes and honest estimation
• Excellent English technical communication; CET overlap; travel to Germany

Responsibilities

• Lead the backend engineering team: direction, estimation, sprint delivery
• Remain hands-on in coding and reviews; tackle hard implementation tasks
• Enforce engineering quality standards and gates
• Design and implement architecture; surface feasibility early
• Deliver the work package roadmap for streaming AI services and guards
• Own release/version management across CI/CD and environments
• Ensure production service reliability with monitoring and incident response
• Run on-call and escalation across time zones
• Support vehicle integration and end-to-end testing with the client
• Contribute to hiring, onboarding, and skill development for the location
• Represent the location in sprint ceremonies and client reviews; maintain docs in Confluence

Skills

8+ years backend engineering

2+ years leading a team of 5–10

Python expertise (FastAPI, asyncio)

Streaming architectures in production

REST and gRPC API development

OAuth2 and mTLS security

PostgreSQL deep expertise

LLM integration in production

Docker and Kubernetes

Azure cloud (AKS/Container Apps)

Terraform/IaC

OpenTelemetry and tracing

Azure DevOps/GitHub CI/CD ownership

Scrum experience

English C1 communication

Willingness to travel to Germany

Tools

FastAPI

Python tooling (pytest, testcontainers, ruff, black, pyright, pydantic)

Azure DevOps Pipelines

GitHub Actions

OpenAI/Azure OpenAI integration

LangChain/LangGraph

Terraform IaC

AKS/Container Apps

CI/CD tooling and automation

Job description

Project description

Our client is advancing its in-vehicle voice assistant into an intelligent, AI-powered companion. Large-language-model capabilities (Azure OpenAI / ChatGPT) have been running in production across vehicles. The goal of the project is to develop a backend which is the cloud AI orchestration service behind this: it receives requests from the vehicle, routes them, orchestrates the LLM, tool services and agents, and returns an answer or action to the car. DXC Luxoft serves as the end-to-end delivery partner, working in a joint product team with the client's engineers on the Azure platform.This is the series development and operations work package - a live platform serving a large vehicle fleet, which extends sprint by sprint the backend features while availability and backward compatibility are maintained. New capability in the pipeline includes streaming across the full ASR → LLM → TTS chain, barge-in, multi-intent handling, a guardrails layer for deterministic vehicle-safe answers, agent routing and new tool integrations.The role is Technical Lead and Location Lead for the engineering team. It is a hands-on delivery leadership role: the person is accountable for what the team ships, for the service running inside its availability and incident targets, and for the technical growth of the location.

Responsibilities

• Lead the backend engineering team (backend, DevOps and AI Ops engineers): technical direction, work breakdown, estimation, sprint commitment and delivery against a continuous feature and maintenance flow.
• Stay hands-on — a meaningful share of the week in code and in review. This role writes the hard parts, not just the tickets about them.
• Own engineering quality standards and their enforcement: design and code review, Python toolchain and quality gates (pytest, testcontainers, ruff, black, pyright, pydantic), test coverage expectations, definition of done.
• Implement the architecture, and push back on it when it won’t survive contact with production: co-author ADRs with the Solution Architect, surface feasibility and operability concerns early, and own the implementation path once a decision is made.
• Deliver the work package roadmap: streaming migration of AI service calls (incremental chat completion, real-time ASR, TTS during synthesis) with buffering, connection management and cancellation; barge-in; multi-intent handling; guardrails and system-prompt enforcement; agent routing; new tool and agent integrations.
• Own release and version management: branch strategy, CI/CD pipeline health on Azure DevOps (incl. self-hosted runners) and GitHub, automated test gates, staged rollout, deployment and rollback.
• Be accountable for the service in production: monitoring, alerting and tracing (Azure Monitor, LangFuse, OpenTelemetry, PagerDuty routing), incident command and resolution inside the 24-hour target, root-cause analysis, stability and performance measures, patch management, and cost/latency optimisation.
• Run 2nd- and 3rd-level support processes for the location during business hours, including the on-call rota, escalation paths and handover discipline across time zones.
• Support vehicle integration and end-to-end testing together with the E2E testing work package, and participate in defect triage across the vehicle/backend boundary.
• Build and grow the location: participate in hiring and technical interviews, onboard new engineers, develop skills across the team, and keep the location's engineering reputation with the client intact.
• Represent the location in sprint ceremonies, technical alignment and client-facing reviews; maintain technical documentation in Confluence and work within the client's requirements management tooling.

SKILLS

Must have

• 8+ years in backend engineering with Python, including 2+ years leading a team of 5–10 engineers as technical lead — with the team's delivery, not just their own, as the measure.
• Still hands-on: expert Python (FastAPI, asyncio), and comfortable owning the hardest implementation in the sprint.
• Experience with streaming architectures in production (SSE/WebSocket/gRPC streaming, buffering, backpressure, cancellation semantics).
• REST and gRPC API development and operation, with OAuth2 and mTLS for secure communication and authorisation.
• PostgreSQL at depth: schema design, tuning, migrations via Alembic; plus practical handling of embeddings for RAG-based LLM queries.
• Hands-on experience integrating LLM APIs into production backends — Azure OpenAI or OpenAI API, LangChain/LangGraph or equivalent, tool/agent workflow orchestration, prompt handling and LLM constraint handling.
• Container orchestration: Docker and Kubernetes (deployment, scaling, secrets/config, networking, load balancing).
• Azure cloud experience (AKS or Container Apps, Managed Identity, Key Vault, Monitor) and Terraform/IaC: reusable modules, environment separation, remote state and locking, CI/CD integration, infrastructure lifecycle management.
• Demonstrable accountability for a production service: monitoring and alert design, distributed tracing with OpenTelemetry, incident management under a resolution SLA/SLO, patch and release management, and the judgement calls that come with being the escalation point.
• CI/CD ownership on Azure DevOps (Repos, Pipelines) and/or GitHub, with automated testing, linting and formatting gates.
• Demonstrable Scrum experience (sprints, reviews, retros, backlog maintenance) and the discipline to keep estimates honest.
• English C1 — daily technical communication with the client's engineers and the onshore team.
• Working-hours overlap with CET sufficient for daily alignment, and willingness to travel to Germany for knowledge transfer, workshops and integration phases — including an intensive onboarding/takeover period at project start.

Nice to have

• Experience taking over a live system from a previous supplier: knowledge transfer under time pressure, reverse-documenting an inherited codebase, stabilising what you did not build.
• Experience building up an offshore location or team from a small core — hiring, onboarding, retention, and establishing credibility with a demanding customer.
• Automotive or in-vehicle software context: MIB3 / E³ / SDV platforms, Android Automotive (AAOS), AIDL, Viwi protocol, vehicle telemetry and configuration services.
• Streaming-level ASR/TTS service integration (Azure Speech, Cerence, Google TTS, Whisper).
• LLM observability and evaluation practice: LangFuse, prompt regression suites, quality metrics (faithfulness, hallucination rate, latency P95, WER/CER).
• Broader persistence experience: MongoDB (pymongo/beanie), CosmosDB.
• Awareness of automotive quality and security frameworks (A-SPICE, ISO/SAE 21434, TISAX) and of privacy-by-design/GDPR constraints on telemetry and logging.
• German language skills.