Senior AI Developer (Construction Technology)
TAKOMAN PTE. LTD. · Singapore ·
- Seniority
- Senior
- Category
- AI engineering
- Experience
- 3+ years
- Visa sponsorship
- Yes
- Salary
- SGD 100,000 – 150,000 / year
TAKOMAN PTE. LTD. · Singapore ·
Build and deploy AI systems for construction tech: autonomous agents, multilingual speech pipelines, RAG for document search, and GPU-optimized model serving.
We are seeking an AI Developer to design, build and deploy intelligent systems that enhance construction operations, safety and productivity across multilingual environments.
Responsibilities:
- Develop and deploy AI-powered autonomous agents and multi-agent orchestration systems for construction project management, using large language models and agentic loop architectures
- Build and maintain end-to-end speech technology pipelines (automatic speech recognition and text-to-speech synthesis) enabling real-time multilingual voice interfaces for field workers and customers, including model deployment on GPU infrastructure, latency optimisation and failover management
- Design and implement retrieval-augmented generation (RAG) systems and automated data management frameworks for construction document repositories (permits, contracts, safety manuals, etc.) with semantic search
- Develop custom MCP (Model Context Protocol) server integrations connecting AI agents to internal construction management databases, IoT sensor feeds and ERP systems
- Manage GPU compute infrastructure for AI model serving, including CUDA environment management, model quantisation, vRAM optimisation and container orchestration
- Research and implement automated CI/CD pipelines for AI model deployment, A/B testing and performance monitoring in production environments
- Create real-time data visualisation dashboards and reporting tools for construction project KPIs powered by AI-driven analytics
- Evaluate and benchmark emerging AI models, maintaining internal documentation on model capabilities, cost-performance trade-offs and deployment readiness assessments
- Provide external AI development consulting services to third-party clients, including requirements analysis, system architecture design, proof-of-concept development and production deployment of custom AI solutions
- Conduct technical feasibility assessments and prepare proposals for client AI projects, covering scope definition, technology stack recommendation, timeline estimation and cost-benefit analysis
- Deliver end-to-end AI system integration for external clients: from system design through development, testing, deployment and post-launch support, with a focus on LLM-powered automation, conversational AI and speech-enabled interfaces
- Represent the company in client-facing technical discussions, pre-sales demonstrations and industry events related to AI and construction technology
- Develop reusable AI solution templates and reference architectures that can be customised for different verticals (construction, property management, facilities maintenance)
Requirements:
- PhD in Computer Science, Electrical Engineering, or closely related field
- Minimum 3 years of hands-on experience building and deploying production AI systems (research prototypes alone do not qualify)
- Demonstrated expertise in BOTH automatic speech recognition (ASR) AND text-to-speech (TTS) system deployment, including model training, fine-tuning, and end-to-end speech pipeline engineering
- Strong proficiency in programming languages such as Python, frameworks such as PyTorch, LangChain, Linux and macOS development environments
- Experience with LLM agent frameworks, prompt and context engineering, harness for agentic AI systems, and real-time system integration
- Proven track record of deploying AI services on bare-metal GPU servers (not just cloud-managed services), including NVIDIA driver management, CUDA toolkit, conda/venv environment isolation
- Working proficiency in both English and Mandarin Chinese (written and spoken) for bilingual system development and communication
- Self-motivated, enthusiastic in research on AI-related fields
- Excellent client-facing communication skills with ability to translate complex AI concepts into actionable business recommendations for non-technical audience
Nice to have:
- Published research in speech processing, NLP or AI-related conferences (Interspeech, ICASSP, ACL, EMNLP, etc.)
- Experience with model post-training, knowledge distillation or model quantization techniques
- Prior exposure to construction, civil engineering or built-environment technology