Presales & AI Solutions Architect - Generative AI & LLM Prototyping

4 days ago

Singapore ST Engineering Full time

At ST Engineering, we apply our technology and innovation to solve real-world problems and improve lives. Our dedication to excellence and our strong track record have earned us a distinctive reputation for quality and trust as a global technology, defence and engineering group. Our diverse portfolio of businesses spans the aerospace, smart city, digital solutions, defence and public security segments. As the Group Engineering Center, we aim to transform the use of technology across all of ST Engineering businesses and push the boundaries of what is possible in the realm of AI to create transformative solutions that impact industries worldwide.

Job Brief (Full-Time)

We are looking for a versatile professional to bridge
AI innovation
with
client engagement
. This role combines
presales activities
such as understanding customer challenges, developing proposals, and showcasing AI capabilities, together with the
technical expertise
to drive prototyping of AI-driven solutions with the AI team.

The ideal candidate must be technically competent while equally comfortable presenting to senior business stakeholders and building hands-on prototypes with modern AI frameworks. This is a strategic role that directly influences client adoption while shaping the early design of scalable AI solutions.

Responsibilities

AI Prototyping & Exploration

  • Solution Design & Ideation: Translate client problem statements into technical hypotheses and conceptual AI architectures. Identify opportunities for applying LLMs, RAG pipelines, and multi-agent frameworks to specific business needs.
  • Rapid Prototyping: Be able to work with AI team to build proof-of-concepts and demos using state-of-the-art external (e.g., LangChain, LlamaIndex, Hugging Face, vector databases) and in house frameworks. Showcase functionality quickly to validate business value and feasibility.
  • Experimentation & Benchmarking: Evaluate different LLMs (GPT, Claude, Llama, Mistral, etc.) and architectures for accuracy, latency, scalability, and cost efficiency. Conduct A/B testing and fine-tuning to optimize results.
  • Data Handling & Integration: Design lightweight data pipelines for ingestion, preprocessing, and embedding generation. Work with structured and unstructured data sources to enable retrieval-augmented generation (RAG) and knowledge mining.
  • Workflow Engineering: Develop agentic workflows that combine reasoning, retrieval, and tool usage. Prototype orchestration layers for decision-making tasks, simulations, or automation of multi-step processes.
  • Evaluation & Governance: Define metrics and perform validation on prototype outputs for reliability, robustness, and alignment with responsible AI practices (bias, explainability, transparency).
  • Documentation & Knowledge

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