AI Engineer
Hyred- Location
- Ho Chi Minh City, Vietnam
- Workplace
- Remote
- Employment
- Full Time
- Salary
- —
Posted 1mo ago
AI Engineer - Hyred | Career Page
AI Engineer
Ho Chi Minh, Ho Chi Minh City, Vietnam
Apply for Position Or refer someone
Job Openings AI Engineer
About the job AI Engineer
Our client is a fast growing Property Tech AI company
About the role
Drive the design, build, deployment, and continuous improvement of agentic AI applications for real estate and construction. You'll own end-to-end agent frameworks, architecting tool chains, crafting prompts, integrating data, and running observability and feedback loops to deliver production-grade AI agents.
Key Responsibilities
- Agent Architecture & Orchestration
- Design and implement agent pipelines using frameworks like LangGraph, Google ADK, CrewAI, etc.
- Wire up external APIs, custom tool calls and endpoint integrations
- Prompt Engineering & Feedback loops
- Develop, iterate, and optimise domain-specific prompt templates at speed
- Embed complex business logic into multi-step prompt workflows
- Build user-feedback pipelines to retrain, fine-tune, and adjust agent behavior
- Secure Deployments
- Containerise and deploy LLMs securely on Azure Cloud (AKS /Azure ML). Familiarity with secure LLM application deployments in Kubernetes clusters.
- Manage CI/CD for model updates and environment provisioning (Terraform)
- Observability & Evals
- Build monitoring and logging for agent performance, latency, failures and error handling.
- Implement agent eval frameworks and track metrics over time (RAGAS, DeepEval/ Langfuse, etc.)
- Collaboration
- Partner with backend & data engineers to deliver end-to-end product
- Document architectures, runbooks and learnings from iterations
Required Skills & Experience
- 4-7 years in data science (ML engineering/computer vision) or software engineering, with over 12 months of LLM production experience
- Hands-on with agentic AI frameworks; strong preference for LangGraph
- Expert prompt engineering skills in complex, domain-specific contexts
- Proven track record deploying models in secure cloud environments. Working experience in the Azure ecosystem is essential.
- Experience with containerization (Docker, Kubernetes) and serverless compute
- Familiarity with observability & eval platforms (Langfuse/LangSmith)
- Ability to translate nuanced business logic into detailed agent workflows and prompts.
- Strong coding skills in Python, plus experience with REST/gRPC API integrations
Nice to have
- Fine-tuning open source models (DeepSeek/Llama/Mistral) for narrow domain based tasks, ensuring higher overall accuracy & consistency
- Prototyping RL-based improvements or RL-as-a-Service experiments
- Prior production exposure to real estate or construction domains in building and deploying any data science application (not necessarily LLM based)
They are an early-stage startup, so you are expected to wear many hats, working with things out of your comfort zone, but with real and direct impact in production.
Why our client?
- Fast-growing, revenue-generating proptech startup
- Steep learning opportunities in real world enterprise production use-cases
- Remote work with quarterly meet-ups
- Multi-market, multi-cultural client exposure
- No BS, get-stuff-done culture. Best practical solution wins.
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- X (Formerly Twitter)
Skills
- Python
- LangGraph
- Google ADK
- CrewAI
- Azure
- Azure ML
- AKS
- Docker
- Kubernetes
- Terraform
- RAGAS
- DeepEval
- Langfuse
- LangSmith
- DeepSeek
- Llama
- Mistral
- REST
- gRPC
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