AI Solution Engineer

About the Role

We are seeking a hands-on AI Solution Engineer to join Amaze's Data & AI team. You will design, build, and deploy Gen AI and AI agent solutions that automate manual tasks, boost employee productivity, and enhance customer experiences — working across the full lifecycle from prototype to production.

Responsibilities

• Build Gen AI applications and autonomous AI agents using LLMs (GPT-4, Claude, Gemini, LLaMA) and agentic frameworks (LangChain, CrewAI, AutoGen)
• Implement RAG pipelines, vector databases, and prompt engineering strategies for accuracy and reliability
• Develop internal AI assistants, intelligent search, and document AI to enhance employee workflows
• Create customer-facing AI solutions including chatbots, recommendation engines, and personalization systems
• Integrate AI solutions with enterprise systems via APIs, microservices, and cloud AI services
• Apply GenAIOps best practices: CI/CD, monitoring, versioning, and evaluation frameworks
• Collaborate with business stakeholders to identify and deliver high-impact AI use cases
• Ensure responsible AI practices: safety guardrails, ethics, data privacy, and governance

Qualifications

• Bachelor's/Master's in Computer Science, AI, Data Science, or related field
• 3+ years in AI/ML or software engineering; 1–2 years in Gen AI / LLM application development
• Hands-on with LLM APIs (OpenAI, Claude, Gemini) and open-source models (LLaMA, Mistral)
• Proficiency in agentic frameworks: LangChain, LlamaIndex, CrewAI, or AutoGen
• Experience with RAG systems and vector databases (Pinecone, Weaviate, ChromaDB, S3 Vector, Google Vertex AI Vector)
• Strong Python skills; REST API development and system integration experience
• Cloud AI experience: AWS Bedrock / SageMaker, or Google Vertex AI / Gemini API
• Familiarity with Docker, CI/CD pipelines, and MLOps practices

Preferred Qualifications

• AWS Bedrock Agents, Amazon Q, or Google Vertex AI Agent Builder experience
• Familiarity with MCP servers for agentic integrations
• Knowledge of data engineering tools (Spark, Kafka, Airflow, Snowflake)
• Strong communication in Thai and English; ability to present AI concepts to business leaders
• Understanding of AI ethics and data privacy frameworks in Thailand/SEA

Core Competencies

• Gen AI & LLM engineering
• AI agent orchestration
• System architecture
• Cloud & MLOps