#EG AI Tech Lead

Company 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.

Job Description

What will you do?

Technical Delivery

• Own end-to-end delivery of AI workstreams: from requirements through data preparation, modelling, integration, testing, and production handover
• Develop agentic applications including RAG pipelines, prompt-engineered agents, and agentic workflows using LangChain, LlamaIndex, LangGraph, or plain Python
• Build on top of GenAI application stacks including LLM orchestration, observability (Langfuse, Braintrust), guardrails, and LLM gateway patterns (LiteLLM, Portkey)
• Implement multi-agent orchestration layer: event routing, resource locking, inter-agent handoff contracts, prompt caching, and shared state management
• Implement agentic design patterns including workflow evaluation, LLM-as-Judge, and AI red teaming
• Adopt Model Context Protocol (MCP) and Agent-to-Agent (A2A) Protocol as foundational extension mechanisms, enabling agents to operate safely across enterprise ecosystems
• Work with AI Solution Architect and Business Analysts on benchmarking and golden-set compilation for agent evaluation
• Implement effective RAG architectures: chunking strategies, embedding selection, vector store configuration (Qdrant, Milvus, pgvector), hybrid search, and reranking
• Build and maintain evaluation harnesses measuring correctness, faithfulness, latency, and safety. Run continuous LLM-as-Judge evaluation on production traces
• Write clean, maintainable Python; participate in code reviews; contribute to shared AI platform libraries

OSS Integration & Data Engineering

• Implement REST, NETCONF/YANG, SNMP trap ingestion, and gNMI streaming telemetry integrations connecting agents to NMS and EMS systems
• Build ServiceNow integrations for ticket read/write, triage updates, change record queries, and human-in-the-loop approval workflow triggers for the Execution Agent
• Build the alarm and telemetry data normalisation pipeline converting multi-vendor OSS data into agent-consumable schemas
• Implement Kafka or equivalent event streaming consumers delivering real-time alarm data to the Alarm Correlation and Ticket Triaging agents
• Work with data and integration engineers to normalise multi-vendor, multi-format network telemetry into consistent schemas the agents can reason over

Safety, Guardrails & Risk

• Implement guardrail architectures: hard limits, soft limits with human confirmation flows, blast radius controls, and escalation logic
• Assist the AI Solution Architect to assess blast radius for each agent — documenting worst-case impacts and designing specific mitigating controls
• Implement and validate rollback procedures for all agent-initiated network actions, including automated rollback triggers based on post-execution KPI degradation
• Work with QA engineers to design and test solutions via defined test cases, and review required improvements
• Ensure all agent architectures comply with IMDA regulatory requirements, AIVerify framework requirements, InfoSec policies, and CMB change governance frameworks

Observability & Evaluation

• Implement the Decision Audit Trail schema for all agents ensuring every decision is fully traceable, explainable, and available for post-incident review
• Build the Agent Operations Dashboard for the NOC team: real-time agent status, decision volumes, accuracy metrics, and exception alerts
• Define and implement the evaluation framework: factual, reasoning, tool-call, retrieval and planning accuracy, confidence thresholds, and human feedback