Backend GenAi Engineer

About Ludeo

Ludeo is a hyper-growth startup in the gaming industry that is revolutionizing the way players discover and engage with games. For the first time, gamers can share their most thrilling gameplay moments with everyone and allow others to PLAY them, not just watch them as video clips.

Ludeo’s vision is to become the world’s first playable social media platform for gamers, enabling seamless discovery and interaction with gaming content.

About the Role

We are seeking a Backend Engineer to join the development of ludeo.ai, our GenAI-powered product that enables users to generate interactive “Ludeos” (gaming experiences) directly from prompts or video content. This is a high-impact role at the intersection of backend architecture, multimodal AI, and real-time systems. You will contribute to the AI engine that transforms unstructured inputs (text/video) into structured, interactive gaming playable moments.

What You’ll Do

Design AI-Native Systems: Design and implement scalable microservices powering complex AI workflows. Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding strategies, and vector database infrastructure (e.g., Pinecone, Weaviate, Milvus, PGVector). Optimize retrieval, prompt orchestration, latency, and cost.
Agentic Workflows: Design and implement multi-agent systems using planner/executor/tool-calling patterns. Implement stateful, multi-step AI workflows with frameworks such as LangChain, CrewAI, AutoGen, or similar. Build evaluation, observability, and safety mechanisms for LLM systems.
Multimodal AI: Integrate multimodal models (vision + text) to understand video and translate it into structured form.
Scale & Infrastructure: Ensure robustness, security, and high availability on AWS/Kubernetes. Contribute to distributed systems that handle real-time data and AI workloads efficiently.
Collaborate: Work closely with Product and Design to translate GenAI capabilities into stable, scalable production features.

Requirements:

Backend Expertise: 5+ years of backend development experience with deep expertise in Python or Node.js and microservices. Strong distributed systems and API design experience.
GenAI Systems Experience: Hands-on experience building production LLM systems. Proven experience with RAG architectures, vector databases, embedding pipelines, and prompt orchestration. Experience designing multi-step or agentic AI workflows.
Infrastructure: Strong experience with AWS and Kubernetes in production environments. Deep knowledge of SQL & NoSQL systems.
Communication: Ability to translate complex AI systems into clear product and business decisions.

Preferred Qualifications

Experience designing autonomous or semi-autonomous AI systems (planner/executor architectures, tool-calling, long-running agents)
Experience evaluating and benchmarking LLM systems (quality, hallucination mitigation, latency, cost optimization)
Strong DevOps capabilities, including Docker, CI/CD pipelines, and deploying AI services/models to production