Senior Software Engineer

Let's introduce ourselves

At Volvo Cars, we are redefining mobility through software. As part of the VC.OS.HI (Volvo Cars High Integrity) initiative, we are building the in-house software capabilities that will power future software-defined vehicles.As an Applied AI Lead Engineer, you will drive AI adoption across one of Volvo Cars' most strategic software programs.

Working at the intersection of AI, software engineering, and automotive innovation, you will transform AI technologies into practical solutions that improve engineering productivity.

This role focuses on delivering production-ready AI solutions used by engineers every day, ensuring security, governance, traceability, and engineering quality while accelerating software development.

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:

• Drive the end-to-end development of applied AI products from concept and architecture through implementation, validation, deployment, and continuous improvement.
• Design and implement modern AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Graph-RAG, knowledge graphs, and agentic AI workflows.
• Build engineering assistants that help developers and architects search, understand, summarize, and act on technical knowledge spanning requirements, architecture artifacts, source code, CI logs, test results, design documents, and operational data.
• Develop AI-enabled solutions that improve software development workflows, including backlog analysis, requirements understanding, code navigation, documentation generation, test support, CI/CD diagnostics, and engineering decision support.
• Define scalable AI architecture patterns covering data ingestion, indexing, retrieval, orchestration, evaluation, monitoring, observability, and secure deployment.
• Partner closely with architects, concept leads, software developers, CI/build teams, and platform organizations to identify and prioritize high-value AI use cases.
• Establish engineering best practices for AI product development, including evaluation methods, prompt engineering, governance, quality assurance, security, and Responsible AI principles.
• Coach and mentor engineers while helping build a sustainable AI engineering capability across VC.OS.HI.
• Measure and demonstrate business impact through improvements in engineering productivity, knowledge reuse, development efficiency, traceability, and developer experience.
• Influence the future AI strategy for software development within Volvo Cars and contribute to the long-term evolution of AI-native engineering ways of working.

What you'll bring

We are looking for a 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.
• Strong hands-on experience with Large Language Models (LLMs) and retrieval-based architectures such as RAG and Graph-RAG.
• Experience building agentic systems, workflow automation solutions, tool-augmented AI applications, or multi-step reasoning workflows.
• Excellent software engineering skills, including Python and/or TypeScript development, APIs, testing strategies, version control, CI/CD pipelines, and maintainable software design.
• Experience designing scalable AI architectures covering retrieval, indexing, orchestration, observability, evaluation, access control, and deployment.
• Ability to translate domain-specific engineering challenges into practical AI solutions that deliver measurable value.
• Strong understanding of Responsible AI principles, security, privacy, intellectual property protection, governance, and enterprise deployment considerations.
• Experience leading technical initiatives, influencing stakeholders, mentoring colleagues, and driving implementation from idea to adoption.

Preferred qualifications:

• Experience building enterprise knowledge assistants, engineering copilots, developer productivity tools, or AI-powered software factory capabilities.
• Knowledge of MLOps, AI evaluation frameworks, telemetry, monitoring, and production AI operations.
• Experience working in software-intensive environments such as automotive, embedded systems, cloud platforms, developer platforms, or large-scale engineering organizations.
• Good to have experience with technologies such as Azure AI, Azure OpenAI, OpenAI APIs, LangChain, LangGraph, vector databases, graph databases, FastAPI, and cloud-native architectures.
• Familiarity with software development life cycle processes, requirements engineering, architecture development, testing, CI/CD, or software factory concepts.
• Experience enabling AI adoption in highly regulated, security-sensitive, or safety-oriented environments.