About Our Client
Our client is a forward-thinking Data & AI consulting firm headquartered in Singapore, delivering impactful solutions across the APAC region. As a strategic partner within the AWS ecosystem, they support enterprises in modernizing their data platforms, adopting AI, and leveraging Generative AI to drive measurable business outcomes.
With a strong focus on practical value and human-centered AI adoption, they work closely with leading organizations across industries such as banking, telecommunications, and retail. By combining deep domain knowledge, trusted partnerships, and an outcome-driven mindset, our client enables businesses to move beyond experimentation and achieve scalable, long-term success with AI.
About the Role
Our client is looking for a GenAI Engineer (3–6 years of experience) to design and develop production-ready AI solutions. This role blends strong software engineering capabilities with hands-on expertise in applied AI, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures.
Key Responsibilities
- Design and deliver scalable AI features using LLMs, RAG pipelines, and agent-based systems
- Build end-to-end RAG workflows, including retrieval techniques, embeddings, vector search optimization, context handling, guardrails, and fallback strategies
- Develop and orchestrate agent workflows using frameworks such as LangChain, LangGraph, or similar tools
- Build and deploy cloud-native services and APIs (REST/gRPC) to support AI applications at scale
- Implement event-driven architectures for real-time AI interactions
- Work with graph databases (e.g., Neo4j, Amazon Neptune) to manage complex data relationships
- Fine-tune models and optimize performance for specific business domains
- Ensure system reliability, including latency optimization, scalability, token efficiency, and cost management
- Set up monitoring, logging, and observability for AI systems, including prompt/model versioning and rollback strategies
- Collaborate with cross-functional teams (data, engineering, product) to deliver high-impact AI solutions
Required Qualifications
- 3–6 years of experience in AI/ML engineering, software engineering, or applied AI roles
- Proven experience building production-grade systems using LLMs, RAG, and agent-based architectures
- Strong programming skills in Python, with additional exposure to Node.js, Java, or Go
- Experience with cloud-native system design, including microservices, REST/gRPC APIs, and event-driven architectures
- Solid understanding of embeddings, vector databases, and retrieval techniques
- Experience with agent orchestration frameworks (e.g., LangChain, LangGraph)
- Knowledge of model fine-tuning and performance optimization
- Hands-on experience with graph databases such as Neo4j or Amazon Neptune
- Strong understanding of system scalability, performance tuning, and cost optimization
- Experience implementing monitoring, debugging, and observability in production environments
- Strong analytical thinking and ability to work effectively in a fast-paced team environment
Preferred Qualifications
- Experience working with cloud platforms such as AWS, GCP, or Azure
- Familiarity with Docker, Kubernetes, and container orchestration
- Knowledge of prompt engineering and evaluation methodologies
- Experience in consulting or client-facing roles
What Our Client Offers
- Impact-driven work: Contribute directly to real-world AI applications and business outcomes
- Career development: Ongoing learning, mentorship, and clear growth opportunities
- Competitive package: Attractive salary, benefits, and performance incentives
- Collaborative culture: Work alongside a high-performing and supportive team
- Global exposure: Opportunities to engage with international projects and travel