Lead Engineer AI

As an experienced Senior Engineer/Assistant Engineering Manager in CARS24's AI Team, your primary role will be to architect, build, and lead the development of robust, scalable AI infrastructure that powers intelligent applications at scale. This is not a data science or AI research role, but rather focuses on building foundational AI platforms and services that enable rapid deployment and operation of AI-powered features by product teams. **Key Responsibilities:** - Design and build scalable AI platforms and services supporting multiple AI/ML use cases across CARS24 - Architect and implement production-grade AI agent systems such as RAG pipelines, vector databases, and LLM orchestration frameworks - Lead the development of synchronous and asynchronous AI service APIs, prioritizing reliability, performance, and cost optimization - Establish engineering best practices, code standards, and architectural patterns for the AI platform team - Mentor junior engineers, contribute to technical decision-making, and collaborate with ML engineers and product teams to translate AI/ML models into production-ready services - Own end-to-end delivery of critical AI platform components from design through deployment and operations **Qualifications Required:** - Core Engineering Expertise: - Deep proficiency in Python with strong knowledge of async programming, type systems, and performance optimization - Strong working knowledge of Java and Spring Boot for building enterprise-grade microservices - 5-6 years of hands-on software engineering experience with a track record of building production systems at scale - AI Platform & Infrastructure: - Understanding of AI agent architectures and orchestration frameworks - Hands-on experience with RAG systems, vector databases, LLM APIs, and building synchronous and asynchronous AI service architectures - Familiarity with LLM streaming patterns using WebSockets, SSE, or gRPC streaming - Software Engineering Fundamentals: - Strong system design skills with the ability to architect scalable, distributed systems - Experience with cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), APIs, microservices, message queues, event-driven architectures, database design, caching strategies, and performance optimization - Proficiency with CI/CD pipelines, monitoring, observability tools This role offers the opportunity to work on cutting-edge AI infrastructure that directly impacts customer experience, shape the technical direction of AI platforms in a rapidly growing unicorn, collaborate with talented engineers, data scientists, and product leaders, and potentially grow into engineering leadership roles as the team scales. As an experienced Senior Engineer/Assistant Engineering Manager in CARS24's AI Team, your primary role will be to architect, build, and lead the development of robust, scalable AI infrastructure that powers intelligent applications at scale. This is not a data science or AI research role, but rather focuses on building foundational AI platforms and services that enable rapid deployment and operation of AI-powered features by product teams. **Key Responsibilities:** - Design and build scalable AI platforms and services supporting multiple AI/ML use cases across CARS24 - Architect and implement production-grade AI agent systems such as RAG pipelines, vector databases, and LLM orchestration frameworks - Lead the development of synchronous and asynchronous AI service APIs, prioritizing reliability, performance, and cost optimization - Establish engineering best practices, code standards, and architectural patterns for the AI platform team - Mentor junior engineers, contribute to technical decision-making, and collaborate with ML engineers and product teams to translate AI/ML models into production-ready services - Own end-to-end delivery of critical AI platform components from design through deployment and operations **Qualifications Required:** - Core Engineering Expertise: - Deep proficiency in Python with strong knowledge of async programming, type systems, and performance optimization - Strong working knowledge of Java and Spring Boot for building enterprise-grade microservices - 5-6 years of hands-on software engineering experience with a track record of building production systems at scale - AI Platform & Infrastructure: - Understanding of AI agent architectures and orchestration frameworks - Hands-on experience with RAG systems, vector databases, LLM APIs, and building synchronous and asynchronous AI service architectures - Familiarity with LLM streaming patterns using WebSockets, SSE, or gRPC streaming - Software Engineering Fundamentals: - Strong system design skills with the ability to architect scalable, distributed systems - Experience with cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), APIs, microservices, message queues, event-driven architectures, database design, caching strategies, an