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Build and optimize large-scale AI search infrastructure, including web crawlers, embedding models, and high-performance vector databases for AI-powered search.
Backend Engineer building scalable AI orchestration frameworks, RAG systems, and cloud-native AI services using Python, PostgreSQL, and vector databases to power enterprise-grade generative AI applications.
Lead a team building AI-powered data pipelines, vector databases, and multi-agent orchestration for fraud detection and risk mitigation at a large-scale platform.
Design and maintain AI-ready data architectures, including vector and graph databases, to power retrieval-augmented generation systems and enterprise analytics for investment and market intelligence.
Design and build AI-ready data platforms and ML pipelines for analytics, GenAI, and RAG systems on AWS/Azure/GCP, ensuring production-grade delivery and MLOps practices.
Builds data pipelines, vector databases, and multi-agent orchestration frameworks for an AI-powered risk engine that enforces trust & safety policies in real time.
Builds and optimizes Go-based microservices and a Neo4j knowledge graph to power a legal reasoning engine, ensuring 2s p95 latency for Singapore’s statutory data pipeline.
Designs and implements cloud data pipelines and AI-driven solutions for clients, integrating vector databases and RAG techniques to meet business goals.
Builds and maintains scalable backend services in Go/Python and integrates ML models into production for AI/LLM-powered products, while also developing React-based UIs.
Build full-stack web apps and integrate AI features using modern stacks (React, Node.js/Python/.NET, SQL/NoSQL) while leveraging AI coding assistants daily.
Build and deploy AI-powered web apps and APIs for a digital asset platform, integrating LLMs, RAG, and agentic frameworks with Java Spring Boot, Kubernetes, and AWS.
Build full-stack web apps and integrate AI features using modern stacks, AI coding assistants, and LLM APIs to deliver enterprise solutions.
Build and maintain SGInnovate’s Deep Tech Central platform using full-stack skills (Next.js, NestJS, PHP, Drupal) and integrate AI features with AWS Lambda, vector databases, and LLM APIs.
Build and deploy scalable AI systems using Python, LLMs, and GenAI to transform documents into knowledge graphs and automate workflows for industrial and automotive clients.
Design and build scalable Python back-end services in cloud environments, lead AI/GenAI initiatives using libraries like TensorFlow and LangChain, and mentor teams on clean code and best practices.
Build and deploy scalable AI systems using LLMs and GenAI, transforming documents into knowledge graphs and automating code analysis with Python and FastAPI.
Builds and scales an AI-driven platform that ingests enterprise data, maps workflows, and automates complex processes using Python, JavaScript, and cloud-native tools.
Build a next-gen AI platform for hardware engineering, owning full-stack features from architecture to deployment while integrating modern LLM workflows and collaborating closely with founders.
Builds and maintains AI-enabled apps, agents, and workflow automations for healthcare workflows, integrating LLMs, RAG systems, and enterprise tools to improve efficiency and knowledge reuse.
Design and maintain enterprise-scale AI platforms, deploying and optimizing LLMs and vision models on NVIDIA SuperPods/Cloud using Kubernetes, Docker, and CI/CD pipelines.
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