Senior AI Engineer

NCS PTE. LTD.; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

NCS PTE. LTD. is seeking an experienced AI Engineer within the Forward Deployed Engineering model to design and run rapid Gen AI experiments, testing prompts, configurations, and retrieval strategies in POC/POV engagements.

You will collaborate with PMs, developers and SMEs to refine data, prompts and evaluation methods. The role requires 6+ years of hands-on experience, familiarity with cloud AI services and agentic orchestration frameworks, and the ability to deliver fast, evidence-based

Qualifications

• 6+ years of hands-on experience, ownership of experimentation strategy across engagements.
• Advises PMs on feasibility and trade-offs; communicates findings to clients.
• Understanding of Gen AI concepts (tokenization, embeddings, RAG, prompting).
• Familiar with major cloud AI services (AWS Bedrock, Vertex AI, Azure AI Foundry).
• Knowledge of China AI models (DeepSeek, Qwen, GLM) is a strong plus.
• Familiarity with agentic orchestration frameworks for multi-step workflows.

Responsibilities

• Understand business problem, POC objectives, evaluation metrics.
• Design experiments: model configurations, prompts, retrieval strategies.
• Analyse Gen AI outputs for quality, accuracy and alignment; identify failures.
• Prepare data samples and build simple data pipelines for experimentation.
• Collaborate with PMs, devs, SMEs; document results clearly.

Skills

Gen AI concepts

Python

Cloud AI

Experimentation strategy

RAG embeddings

Prompting

LLMOps

Model evaluation

China models

Agentic orchestration

Tools

AWS Bedrock

Vertex AI

Azure AI Foundry

LangGraph

Strands

Vector DBs

Job description

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of Industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

This role sits within NCS AI Central's (AIC) Forward Deployed Engineering (FDE) model - the combined capability that takes AI solutions from proof-of-concept through to hardened production systems. As AI Engineer, you design and run rapid experiments on Gen AI models, prompts, and retrieval strategies to give the squad fast, evidence-based answers on model performance - operating primarily within fast-moving FDE engagements (POC/POV, pilot deployments).

Note on role boundaries: this role is the FDE-focused counterpart to the practice's AI/LLM Specialist role. AI Engineer runs rapid experimentation and prototyping during POC/POV to give the squad fast, evidence-based answers; AI/LLM Specialist owns the deeper evaluation harness design, prompt/fine-tuning discipline, and production-quality rigor once an engagement scales. The two roles work together across the lifecycle rather than duplicating each other. This role is also distinct from Data Scientist, who applies classical statistical/ML methods and builds the quantitative baseline that any Gen AI solution must beat.

What will you do?

Experimentation & Evaluation

• Understand the business problem, POC objectives, and evaluation metrics.
• Design experiments to test different model configurations, prompts, or retrieval strategies.
• Analyse Gen AI outputs for quality, accuracy, and alignment with requirements; identify common failure modes (hallucination, bias, irrelevant answers, factual errors).
• Support SMEs in defining ground truth benchmarks for evaluation.

Data Preparation & Pipelines

• Profile and clean sample datasets for experimentation (lightweight data prep).
• Build and test simple pipelines for data ingestion, prompt construction, and output evaluation.

Gen AI & Agentic Techniques

• Work with foundation models via AWS Bedrock, Google Vertex AI, or Azure AI Foundry depending on engagement cloud posture.
• Apply working knowledge of China-origin models (DeepSeek, Qwen, GLM) as increasingly relevant, cost-effective alternatives.
• Apply agentic orchestration frameworks such as AWS Strands, LangGraph, or equivalent, for designing and testing multi-step agent workflows.
• Apply prompt strategies, prompt engineering patterns, and RAG design (chunking, embeddings, retrieval evaluation); support ingesting/vectorising content to knowledge bases.
• Provide insights and recommendations to improve model performance in quick iterations, including fine-tuning approaches where applicable.

FDE & Development/Maintenance Coverage

• During FDE engagements: rapidly test candidate models, prompts, and retrieval strategies, giving the team fast, evidence-based go/no-go signals.
• During system development & maintenance engagements: support ongoing model/prompt tuning and monitoring as applications move toward production.

Collaboration

• Collaborate with developers on integrating models into the POC workflow, and work closely with PM, devs, and SMEs to refine data and prompts.
• Partner with the Data Scientist on evaluation methodology where classical statistical baselines are in play, and with the AI/LLM Specialist when an engagement moves toward production-grade evaluation.
• Document experiments briefly but clearly (hypothesis result conclusion).

The ideal candidate should possess:

• 6+ years of hands-on experience, including prior ownership of experimentation strategy for complex or ambiguous problem statements. Sets the experimentation approach across multiple engagements and mentors junior AI Engineers.
• Advises PMs and stakeholders directly on feasibility and experimentation trade-offs; represents technical experimentation findings in client conversations.
• Understanding of Gen AI concepts (tokenization, embeddings, RAG, prompting, evaluation).
• Familiar with at least one major cloud AI service (AWS Bedrock, Google Vertex AI, or Azure AI Foundry); working knowledge of others a plus.
• Working knowledge of the China AI model landscape (DeepSeek, Qwen, GLM) a strong plus.
• Familiarity with agentic orchestration frameworks (AWS Strands, LangGraph, or equivalent), for designing and testing multi-step agent workflows.
• Ability to do rapid experimentation rather than perfect models.
• Generative AI Leader or Machine Learning Engineer certification, or equivalent.
• Exposure to LLMOps practices (model monitoring, versioning) for production transition.
• Familiarity with model fine-tuning techniques.
• Exposure to regulated government cloud environments.
• Basic proficiency in Python and Gen AI tools (e.g., model SDKs, vector DBs).
• Analytical minds