Senior Software Engineer

Careem’s ML Platform & GenAI Applications team sits at the intersection of engineering, data science, and product innovation. We provide the core tooling that enables various verticals—Ride-Hailing, Food, Groceries, Pay, and more—to deliver intelligent, delightful experiences powered by Machine Learning and Generative AI. As a Senior Software Engineer on this team, you’ll be a hands-on technical leader: designing distributed systems, hardening new GenAI workflows, and ensuring product teams can easily transition from prototypes to production while maintaining Careem-class standards for reliability, cost-efficiency, and responsible AI.

Responsibilities

• Design and build reusable services, APIs, and workflows that facilitate the prototyping, testing, and launching of GenAI-driven features
• Co-create flagship GenAI applications, such as RAG-powered help-center answers, driver-partner copilots, or marketplace-level demand forecasting assistants
• Influence architecture to keep the platform reliable, secure, and cost-effective while adding new capabilities like prompt versioning, model evaluation dashboards, or real-time feedback loops
• Champion MLOps & Responsible AI by establishing guardrails, monitoring, and safe-launch practices, allowing experiments to reach production confidently
• Mentor teammates and share learnings through design reviews, mini-workshops, and internal demos
• Collaborate with designers, product managers, and data scientists to transform vague product ideas into well-scoped engineering work

Requirements

• 7+ years of hands-on experience in software development with a solid foundation in principles and design practices
• Strong expertise in Python, Java, Go, or similar programming languages
• Hands-on experience with GenAI and ML platforms, including fine-tuning transformers, managing embeddings, or rolling out RAG pipelines
• Working knowledge of vector databases (Pinecone, Milvus, Weaviate) and model-aware search
• Strong foundations in software design, networking, security, observability, and CI/CD
• Experience with cloud control planes (AWS, GCP, etc.) or database internals, including query optimization
• Proven ability to drive projects from inception to production and mentor other engineers
• Experience with ML platform and MLOps is essential