Lead AI Engineer / AI Solutions Architect (Remote)

Application Process

https://forms.gle/4Hdj8CqbWjufQxAdA

About Us

Hipster Inc. is a Singapore-headquartered technology company building enterprise software, AI solutions, cloud platforms and digital products for businesses and government organisations.

We also developed Voncierge, our own AI-powered customer engagement platform, deployed at Changi Airport and Jewel Changi. Voncierge connects customers with AI agents or live representatives through web, mobile, WhatsApp, kiosks and other digital channels.

We are expanding Voncierge into an enterprise AI agent platform capable of understanding customer requests, retrieving information, executing business workflows and integrating with enterprise systems.

Alongside Voncierge, Hipster delivers custom AI and enterprise technology solutions through commercial projects, government tenders and open innovation programmes.

The Role

We are looking for a hands-on Lead AI Engineer / AI Solutions Architect who can design, build, deploy and scale enterprise-grade AI systems.

You will take technical ownership of AI architecture across both Voncierge and Hipster, working on everything from conversational AI agents and enterprise workflow automation to secure cloud infrastructure and open-source model customisation.

This is not a research-only or prompt-engineering role. You must be capable of independently designing system architecture, writing production code, deploying solutions and solving complex technical challenges.

You will work closely with our CEO, product managers, designers and engineering teams to turn AI concepts into reliable, commercially viable products.

Key Responsibilities1. Enterprise AI Architecture & Engineering

• Design and build secure, scalable, multi-tenant AI systems for enterprise and government clients.
• Own end-to-end architecture, from technical design and model selection to deployment and optimisation.
• Develop production-grade AI services, backend APIs and integrations.
• Build reusable AI components and frameworks for deployment across multiple products and customers.
• Make architectural decisions considering performance, scalability, security, latency and cost.

1. AI Agents & Workflow Automation

• Build intelligent AI agents capable of reasoning, tool calling, API execution and multi-step workflow automation.
• Implement agent orchestration using LangGraph, LangChain, LlamaIndex or similar frameworks.
• Design agent memory, context management, state persistence, human approvals and escalation workflows.
• Integrate agents with CRM, ERP, booking systems, payment platforms, ticketing systems and enterprise APIs.
• Build multilingual AI solutions for web, mobile, WhatsApp, voice and kiosk environments.
• Develop AI agents that perform real business transactions rather than simply answer questions.

1. LLMs & Open-Source Model Customisation

• Evaluate and integrate commercial AI models, including OpenAI, Anthropic, Gemini and AWS Bedrock.
• Deploy, configure and customise open-source models such as Llama, Qwen and Mistral.
• Apply fine-tuning techniques such as LoRA, QLoRA and PEFT where appropriate.
• Work with Hugging Face, vLLM and other model deployment and inference frameworks.
• Optimise model performance, accuracy, latency, GPU utilisation and inference costs.
• Evaluate self-hosted, cloud-hosted and private AI deployments based on customer requirements.
• Determine when RAG, fine-tuning, prompting or conventional software engineering provides the best solution.

1. RAG, Knowledge Systems & Document Intelligence

• Architect enterprise RAG systems using structured and unstructured data.
• Implement embeddings, vector databases, hybrid search, reranking and knowledge retrieval.
• Work with technologies such as pgvector, Qdrant, OpenSearch, Pinecone or similar platforms.
• Build secure, tenant-isolated knowledge bases with appropriate access controls.
• Develop document processing solutions involving OCR, PDF extraction, semantic search and AI-powered analysis.
• Support AI-driven tender analysis, requirement extraction, proposal generation and enterprise document automation.

1. Cloud Architecture & Enterprise Security

• Design and deploy AI infrastructure primarily on AWS, with knowledge of Azure or other cloud platforms.
• Work with services such as AWS Bedrock, SageMaker, Lambda, ECS/EKS, RDS, S3, IAM and VPC.
• Implement Docker, Kubernetes, CI/CD pipelines and infrastructure as code.
• Design secure c…