Senior AI Engineer (Contact Centre)

NCS Group; Singapore; On-site; SGD 80,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation

Professional development support

Collaborative work environment

Job summary

NCS Group in Singapore is seeking a Senior AI Engineer to lead and deliver advanced AI solutions. You will work closely with clients, manage small teams, and drive implementation across various sectors.

The ideal candidate has 5–8 years of AI engineering experience, strong Python skills, and the ability to engage stakeholders effectively. Join a leading AI Tech Services company that offers competitive compensation and opportunities for professional growth.

Qualifications

• 5–8 years of hands-on AI/ML engineering or data science experience with at least 2–3 years in client-facing roles.
• Proven delivery of complex AI projects end-to-end in a consulting environment.
• Strong Python programming skills with frameworks like Pandas, NumPy, and ML libraries.

Responsibilities

• Lead end-to-end delivery of AI workstreams from requirements to production handover.
• Design and build advanced agentic AI solutions including multi-agent systems.
• Serve as a technical point of contact for client teams.

Skills

Python programming

AI/ML engineering

Client engagement

Data science

GenAI applications

Education

Degree in Statistics, Computer Science, Engineering, or Data Science

Tools

Pandas

NumPy

PyTorch

TensorFlow

Docker

Job description

NCS is a leading AI Tech Services company with a 15,000-strong team across the Asia Pacific. We scale our platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries, transforming technology services delivery by combining AI with digital resilience to drive real business impact.

Job Description

As a Senior AI Engineer at NCS, you will be a technical leader operating at the intersection of engineering excellence and client partnership. You will lead end‑to‑end delivery of AI workstreams, design and build advanced agentic AI solutions, and serve as the credible technical face of NCS AI capabilities in client engagements. In addition to strong hands‑on AI engineering, you will lead small technical teams, engage clients with confidence, translate business problems into sound AI architectures, mentor junior engineers, own delivery workstreams, guide your squad, and drive successful implementation of next‑generation AI‑powered solutions across government, telco, financial services, and e‑commerce sectors.

What Will You Do?

Technical Delivery & AI Solution Development

• Lead end‑to‑end delivery of AI workstreams from requirements through data preparation, modelling, integration, testing, and production handover
• Design and build advanced agentic AI solutions including multi‑agent systems, RAG pipelines with AI memory, planning and reasoning loops, and reflection patterns
• Architect GenAI application stacks including LLM orchestration layers, observability tools (Langfuse, Braintrust), guardrails, and LLM gateway patterns (LiteLLM, Portkey)
• Develop production‑grade ML systems alongside GenAI components, maintaining quality across both paradigms
• Design, build, and deploy end‑to‑end ML models (classification, regression, time‑series, NLP) and integrate them into production systems
• Develop GenAI applications including RAG pipelines, prompt‑engineered chatbots, and lightweight agentic workflows using frameworks such as LangChain, LlamaIndex, LangGraph, or plain Python
• Implement effective RAG architectures including chunking strategies, embedding selection, vector store configuration (Qdrant, Milvus, pgvector), and retrieval evaluation
• Build and maintain evaluation harnesses for AI system quality — correctness, faithfulness, latency, and safety

Engineering Excellence & Quality Assurance

• Conduct technical code reviews, enforce engineering standards, and introduce tooling that improves team velocity
• Write clean, maintainable Python code; participate in code reviews; contribute to shared libraries and internal AI platform components
• Design multi‑component AI architectures and communicate them via clear diagrams and written specifications

Client & Stakeholder Engagement

• Serve as a primary technical point of contact for client teams in day‑to‑day delivery interactions
• Lead or co‑facilitate client workshops including requirements discovery, solution walkthroughs, sprint demos, and retrospectives
• Translate ambiguous client requirements into well‑defined technical user stories and acceptance criteria
• Communicate technical trade‑offs and design decisions in clear, accessible language appropriate for business stakeholders
• Manage client expectations proactively, surface risks early, and propose mitigations

Team Leadership & Mentorship

• Technically lead a small squad of 2–4 AI engineers; delegate tasks, review outputs, and coach on best practices
• Mentor junior AI engineers on both technical skills and professional conduct in client settings
• Contribute to internal knowledge‑sharing through technical guidelines, lunch‑and‑learns, and building reusable AI platform components

Qualifications

Required Experience & Background

• 5–8 years of hands‑on AI/ML engineering or data science experience, with at least 2–3 years in client‑facing or technical‑lead roles
• Proven delivery of complex AI projects end‑to‑end in a professional services, consulting, or systems integration environment
• Demonstrable agentic AI project experience with systems incorporating RAG, AI memory, reflection, planning, and/or reasoning patterns

Core Technical Competencies

• Strong Python programming with Pandas, NumPy, Scikit‑learn, PyTorch or TensorFlow; comfortable writing modular, testable code
• Solid understanding of ML fundamentals including feature engineering, model evaluation, bias‑variance trade‑off, and hyperparameter optimisation
• Hands‑on GenAI experience building RAG chatbots and applications, working with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or equivalent)
• Familiarity with vector databases and embedding models for semantic search and retrieval (e.g., Qdrant, Milvus, pgvector)
• Experience with at least one cloud platform (AWS, Azure, or GCP) for model training or deployment
• Proficiency with Git, CI/CD, and containerisation (Docker); familiarity with MLOps practices
• Proficiency in at least one additional programming language beyond Python (e.g., TypeScript/JavaScript, Java, Go, or advanced SQL)
• Deep hands‑on experience with agentic frameworks such as LangGraph, CrewAI, AutoGen, or OpenAI Agents SDK
• Experience with LLM observability, evaluation, and guardrails tooling in production environments
• Comfort with multiple programming languages and full‑stack awareness (APIs, front‑end integration, data pipelines)
• Working knowledge of MLOps and AI infrastructure including model serving, monitoring, and CI/CD for AI systems

Client Engagement & Communication Skills

• Proven experience engaging directly with client stakeholders — including non‑technical business owners — on AI solution design and delivery
• Strong written and verbal communication skills; able to produce client‑ready documentation, presentations, and technical specifications
• Experience managing small delivery teams and coordinating across cross‑functional groups

Preferred Qualifications (Nice‑to‑Have)

• Experience building voice AI bots using a pro‑code approach (Amazon Connect, Twilio, Deepgram, Whisper / ElevenLabs + custom orchestration, or LiveKit)
• Experience with MCP (Model Context Protocol) for tool integration in enterprise agentic systems
• Familiarity with responsible AI frameworks such as NIST AI RMF, MAS TRM, or equivalent governance standards
• Exposure to red‑teaming and AI safety testing (OWASP LLM Top 10, promptfoo, adversarial prompt evaluation)
• Presales support experience including contributing to proposals, RFP responses, or solution scoping
• Domain experience in government, financial services, telco, or e‑commerce AI use cases
• AWS, Azure, or GCP certifications (ML or AI specialty) are preferred but not mandatory

Education Qualification

• Degree in Statistics, Computer Science, Engineering, Data Science, or equivalent quantitative discipline

Why Join NCS

• Lead high‑impact Data & AI advisory programs for major enterprises and public sector clients
• Shape enterprise strategies and governance frameworks that drive real transformation
• Work with a talented, multidisciplinary team in a collaborative environment
• Competitive compensation and strong professional development support