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Data Engineer Neo4J
Design and optimize Neo4j graph models for banking data to detect fraud patterns using GDS algorithms, then build real-time dashboards for Risk and AML teams.
Fullstack Engineer (AI Engineer)
Build and deploy production-grade AI systems, integrating LLMs, vector databases, and agent frameworks to operationalize machine learning and generative AI solutions.
Full Stack Technical Lead (AI + Google)
Lead full-stack AI projects on Google Cloud, designing scalable systems with LLMs, RAG, and multi-agent architectures while mentoring teams and enforcing AI-assisted development standards.
Principal Full Stack Engineer (AI Systems)
Architect and build AI-powered workflows for SME back-office automation using LLMs, embeddings, and intelligent agents, while mentoring engineers to adopt AI-assisted development practices.
Software Full Stack Engineer
Build and deploy full-stack AI systems for Singapore’s public housing agency, integrating LLMs, RAG pipelines, and agentic workflows into production-grade web apps and APIs.
Backend Engineer, AI (Remote)
Backend Engineer builds and maintains AI-powered services, APIs, and pipelines that connect models to customer apps using Python, Node.js, and modern AI stacks.
AI-Driven Full-Stack Engineer for Production Apps
Build and deploy AI-powered full-stack applications using LLMs, embeddings, and RAG patterns, hardening them for production with cloud deployments.
M55 - Full Stack Engineer
Build and harden AI-enabled applications (chatbots, RAG, agents) from prototype to production, integrating Azure AI services and ensuring security, compliance, and observability.
Full Stack Engineer 0807-3
Build production-grade AI applications from prototypes, refactoring prototypes into secure, scalable solutions using Azure AI services, full-stack development, and responsible AI patterns.
Backend Engineer (AI Infrastructure & Inference)
Build and maintain backend services, inference pipelines, and orchestration layers for an AI-native product that automates conversations and workflows.
Software Backend Engineer
Builds and maintains scalable backend services and cloud-native APIs for government projects using AWS, Java/Spring Boot or Node.js, and CI/CD pipelines.
AI/ML Engineer (R-00194)
Build and deploy AI/ML models and RAG systems in AWS GovCloud for secure government workflows, using Python and FedRAMP-authorized services while ensuring compliance and Zero Trust security.
Senior FullStack Developer (AI, Product, Node/React)
Build and own AI-powered internal products and automation platforms end-to-end using Node/React, LLM integrations, and production reliability practices.
AI Engineer
Build and scale LLM-powered analytics features for healthcare data, including RAG, text-to-SQL, and agent workflows on AWS and Snowflake.
AI & Data - AI Lab: AI Engineer - Agentic & Generative Intelligence - Senior/Assistant Manager
Build and deploy LLM-driven AI agents and generative solutions using Azure OpenAI, LangChain, and Hugging Face, focusing on RAG pipelines, multi-agent systems, and responsible AI.
AI & Data - Forward Deployed AI Engineer, Manager
Build and deploy enterprise-grade AI systems for clients, leading from prototype to production with LLMs, RAG, agents, and MLOps in regulated environments.
AI & Data - Forward Deployed AI Engineer, Senior Manager
Senior AI engineer embeds and deploys enterprise-grade AI systems for clients, building LLM/RAG pipelines, agents, and ML models while navigating compliance and legacy systems.
CoachMePlus - Senior Software Engineer (AI/ML)
Build and integrate AI/ML features into a human-performance platform, using cloud-native services (AWS Lambda, Bedrock) and modern web stacks (PHP/Symfony, React) to deploy generative AI workflows and intelligent backends.
Senior Machine Learning Engineer
Builds and deploys large-scale AI systems for ZoomInfo’s data platform, including recommendation engines, NLP models, and agentic workflows using LLMs, vector search, and MLOps pipelines.
Senior Full Stack .Net Developer - Cape Town - Remote
Build and scale a global SaaS platform using .NET Core, TypeScript, and AWS, while integrating LLMs to enhance conversational voice intelligence products.