Senior Software Engineer

Company description:

Who are we?Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent. We are constantly pushing our own skills and abilities to drive change in the automobile industry like never before. We are looking for innovative, committed people to join us in this endeavour and create safe, sustainable and connected cars. We believe in the power of people and will challenge and support you to reach your full potential. Join us and be part of Volvo Cars’ journey into the future.

Job description: Let's introduce ourselves

At Volvo Cars, we are on a journey to redefine mobility through software. As part of this transformation, the VC.OS.HI (Volvo Cars High Integrity) initiative is building critical in-house base software capabilities that will power the next generation of software-defined vehicles.We are therefore establishing a practical AI-native engineering capability focused on solving real engineering problems, accelerating developer productivity, improving knowledge access, and enabling better decision-making across the software lifecycle.

As an Applied AI Lead Engineer, you will help shape how AI is adopted inside one of Volvo Cars' most strategic software programs. You will work at the intersection of AI, software engineering, developer productivity, and automotive innovation, translating advanced AI technologies into tangible engineering value.

What you'll do

As an Applied AI Lead Engineer, you will lead the design and industrialization of AI capabilities that enhance engineering effectiveness across Volvo Cars.You will:

• Lead applied AI solutions from concept and architecture through implementation, validation, deployment, and continuous improvement. 

• Design solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Graph-RAG, knowledge graphs, and agentic AI workflows. 

• Build AI assistants that help engineers use knowledge across requirements, architecture, source code, CI/CD, testing, design documents, and operational data. 

• Improve development workflows through AI-enabled backlog and requirements analysis, code navigation, documentation, testing, diagnostics, and decision support. 

• Define scalable AI architectures covering data ingestion, indexing, retrieval, orchestration, evaluation, observability, and secure deployment. 

• Partner with architects, concept leads, developers, CI/build teams, and platform organizations to prioritize high-value use cases. 

• Establish best practices for evaluation, prompt engineering, governance, quality assurance, security, and Responsible AI. 

• Mentor engineers and help build sustainable AI engineering capability across VC.OS.HI. 

• Measure impact through productivity, knowledge reuse, development efficiency, traceability, and developer experience. 

• Contribute to Volvo Cars’ long-term AI strategy and AI-native engineering ways of working. 

Profile description: What you'll bring

We are looking for a hands-on technically strong and curious AI engineer who enjoys converting complex engineering challenges into practical solutions with measurable impact.

You likely have:

Required qualifications:

• Proven experience delivering AI-enabled products, platforms, or engineering solutions used by real users in production or production-like environments.
• Experience with LLM-based applications, including RAG, agentic AI, and tool-integrated systems.
• Hands-on experience with self-hosted models, model serving, inference optimization, and GPU resource management.
• Understanding of AI safety and reliability challenges, including tool misuse, context drift, retry loops, and guardrails.
• Experience building production-grade AI systems with scalability, observability, fault tolerance, and maintainability in mind.
• Knowledge of advanced retrieval architectures, including vector databases, knowledge graphs, hybrid search, reranking, and RAG pipelines.
• Experience designing multi-agent and multi-step workflows with state management, memory, orchestration, and recovery mechanisms.
• Ability to work across the full AI engineering lifecycle, from experimentation and evaluation to deployment, monitoring, and optimization.
• Strong software engineering and collaboration skills, translating AI innovations into reliable production solutions.

Preferred qualifications:

• Experience building enterprise knowledge assistants, engineering copilots, developer productivity tools, or AI-enabled software factory capabilities. 
• Knowledge of MLOps, AI evaluation frameworks, telemetry, monitoring, and production AI operations. 
• Experience in automotive, embedded systems, cloud platforms, developer platforms, or large-scale engineering organizations. 
• Familiarity with Azure AI, Azure OpenAI, OpenAI APIs, LangChain, LangGraph, vector or graph databases, FastAPI, and cloud-native architectures. 
• Understanding of requirements, architecture, testing, CI/CD, and software development lifecycle processes. 
• Experience enabling AI in regulated, security-sensitive, or safety-oriented environments.