Senior AI Engineer (Contact Centre) at NCS3

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. Beyond your strong hands-on AI engineering capabilities, you will lead small technical teams, engage clients with confidence, translate business problems into sound AI architectures, and mentor junior engineers. You will own delivery workstreams, guide your squad, and drive the 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 safetyEngineering 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 specificationsClient & 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 mitigationsTeam 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