Senior AI Engineer

About ST Engineering

ST Engineering is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange.

Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers.

About our Line of Business – Mission Software & Services

Our Mission Software & Services business provides leading-edge mission critical command, control, and communications (C3) systems with secured IT infrastructure and managed services. We support our client’s innovation journey through design thinking, analytics, and AI-enabled decision support with our full suite of cloud computing solutions. We provide intelligent, actionable insights and sustainable solutions to our valued partners in diverse industries including defence, government, and commercial sectors.

Together, We Can Make A Significant Impact

We are seeking an experienced Senior AI Engineer (Agentic AI & Retrieval-Augmented Generation) to join our dynamic team. As a Senior AI Engineer, you will play a key role in designing, developing, and deploying next-generation AI systems powered by Large Language Models (LLMs), Agentic AI frameworks, multi-agent systems, and Retrieval-Augmented Generation (RAG) architectures. Your expertise will contribute to the delivery of mission-critical AI solutions that transform how organizations access knowledge, automate workflows, and augment human decision-making.

Be Part of Our Success

• Design, develop, and deploy Agentic AI solutions leveraging Large Language Models (LLMs), planning agents, tool-using agents, and multi-agent orchestration frameworks.
• Design and implement Retrieval-Augmented Generation (RAG) systems that integrate enterprise knowledge bases, vector databases, document repositories, and external data sources.
• Collaborate with customers, domain experts, and stakeholders to translate business requirements into AI-enabled solutions and intelligent workflows.
• Develop AI microservices, APIs, and backend services to support scalable deployment of generative AI and agentic applications.
• Build and optimize document ingestion, indexing, embedding, retrieval, reranking, and knowledge-grounding pipelines.
• Evaluate, select, and integrate state-of-the-art LLMs, foundation models, embeddings models, and AI agent frameworks.
• Design prompts, agent workflows, tool chains, and memory management mechanisms to improve AI system accuracy and user experience.
• Implement model evaluation, benchmarking, guardrails, observability, and monitoring mechanisms to ensure reliability, safety, and performance.
• Collaborate with software engineers and DevSecOps teams to deploy AI solutions into production environments using CI/CD best practices.
• Optimize AI system performance, latency, scalability, and operational costs.
• Conduct proof-of-concepts, technology evaluations, and experiments on emerging AI technologies and frameworks.
• Support pre-sales activities, proposal development, technical presentations, and customer demonstrations.
• Mentor junior engineers and contribute to best practices in AI engineering, software development, and solution architecture.
• Stay abreast of recent developments in Generative AI, Agentic AI, RAG architectures, multimodal AI, and AI engineering practices.

Qualities We Value

• Shall have at least three (3) years of hands-on implementation and deployment experience in artificial intelligence, machine learning, or generative AI solutions.
• Strong experience in Python programming and software engineering best practices.
• Practical experience developing and deploying LLM-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures, vector databases, embeddings, semantic search, and knowledge retrieval pipelines.
• Familiarity with modern LLMs and foundation models from OpenAI, Azure OpenAI, Anthropic, Google, Meta, Mistral, or equivalent ecosystems.
• Experience integrating AI solutions with structured and unstructured enterprise data sources, document repositories, APIs, and knowledge management systems.
• Strong knowledge of prompt engineering, model evaluation, fine-tuning, agent orchestration, and AI workflow design.
• Experience with cloud-native AI development on Azure, AWS, or Google Cloud Platform.
• Experience with containerisation and orchestration technologies such as Docker, Kubernetes, and Microservices Architecture.
• Knowledge of DevSecOps methodologies, CI/CD pipelines, and MLOps/LLMOps practices.
• Familiarity with databases and vector stores such as PostgreSQL, MongoDB, Elasticsearch, Milvus, Pinecone, Weaviate, Chroma, or Azure AI Search.
• Preferably have completed at least one (1) project using Scrum or equivalent Agile development framework.
• Experience in AI governance, responsible AI, model risk management, or AI assurance practices would be advantageous.