Job Description
Position: AI Solution Architect
Position type: Full-time
Working location: Di An, Binh Duong
Working time: 9:00 – 18:00 (Mon – Fri) (Fulltime)
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Responsibilities
- Design and define end-to-end AI Agent architectures for enterprise applications, ensuring scalability, reliability, and security.
- Collaborate with stakeholders (Product, Business, Data, Engineering, DevOps) to translate business requirements into agent-driven solutions.
- Evaluate, select, and integrate foundation models (LLMs, multi-modal) as reasoning engines and orchestrators for AI Agents.
- Architect and implement agent orchestration pipelines (tool integration, memory, planning, multi-agent collaboration) with vector databases and knowledge bases.
- Define data and context retrieval strategies to ensure agents work with high-quality, compliant knowledge sources.
- Provide technical leadership across the agent lifecycle: prompt engineering, fine-tuning, evaluation, deployment, monitoring, continuous improvement.
- Lead adoption of MLOps/AgentOps practices (CI/CD for agents, monitoring, observability, safety guardrails) to ensure reliable production systems.
- Stay updated with emerging trends (autonomous agents, multi-modal reasoning, tool-augmented LLMs) and guide adoption.
Job Requirements
Mandatory
- Bachelor’s or Master’s in Computer Science, AI/ML, Data Engineering, or related field.
- 5+ years in AI/ML solution design and deployment, with at least 2 years in an architect or technical lead role focused on LLMs or agents.
- Strong expertise in Python and deep learning frameworks (PyTorch, TensorFlow)
- Proven experience architecting and deploying AI Agents, RAG-based assistants, or LLM applications at scale.
- Hands-on with agent orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and vector databases (Pinecone, Weaviate, FAISS).
- Solid understanding of cloud AI platforms (AWS Bedrock, GCP Vertex AI, Azure OpenAI/ML) and containerization (Docker, Kubernetes).
- Proficiency in MLOps/AgentOps tools (MLflow, W&B, Guardrails, OpenAI Evals).
- Excellent communication and stakeholder management skills in English.
Nice to Have
- Knowledge of multi-agent architectures and coordination patterns.
- Familiarity with API design (REST/gRPC, GraphQL) and integration into enterprise or developer tools.
- Experience with advanced embeddings and structured knowledge representation (knowledge graphs, syntax-aware embeddings).
- Practical experience optimizing inference latency and cost-performance in GPU/TPU clusters for agent workloads.
- Open-source contributions or publications on AI Agents, LLMOps, or multi-agent systems
How To Apply
Step 1: Submit Your CV
Apply directly through the Innotech Vietnam Corporation website by uploading your updated CV to the careers section.
Step 2: Phone Screening
If shortlisted, you will receive a call from the HR team for a brief survey and initial screening.
Step 3: Interview
Qualified candidates will be invited to an interview to further assess suitability for the role.
Step 4: Onboarding
Successful applicants will receive an offer and begin the onboarding process to officially join the team.
