Careem’s ML Platform & GenAI Applications team sits at the intersection of engineering, data science, and product innovation. We provide the core tooling that lets every vertical — Ride-Hailing, Food, Groceries, Pay, and more — 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 making it effortless for product teams to move from prototype to production while meeting Careem-class standards for reliability, cost-efficiency, and responsible AI.
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What you’ll do
- Design and build reusable services, APIs, and workflows that make it simple for product teams to prototype, test, and launch 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: 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, establish guardrails, monitoring, and safe-launch practices so experiments can reach production with confidence
- Mentor teammates and share learnings through design reviews, mini-workshops, and internal demos
- Collaborate widely with designers, product managers, and data scientists to convert fuzzy 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 — 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 platforms and MLOps is a must
