About this role
What will you do?
Technical Delivery
Own end-to-end delivery of AI workstreams: from requirements through data preparation, modelling, integration, testing, and production handoverDevelop agentic applications including RAG pipelines, prompt-engineered agents, and agentic workflows using LangChain, LlamaIndex, LangGraph, or plain PythonBuild 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 managementImplement agentic design patterns including workflow evaluation, LLM-as-Judge, and AI red teamingAdopt Model Context Protocol (MCP) and Agent-to-Agent (A2A) Protocol as foundational extension mechanisms, enabling agents to operate safely across enterprise ecosystemsWork with AI Solution Architect and Business Analysts on benchmarking and golden-set compilation for agent evaluationImplement effective RAG architectures: chunking strategies, embedding selection, vector store configuration (Qdrant, Milvus, pgvector), hybrid search, and rerankingBuild and maintain evaluation harnesses measuring correctness, faithfulness, latency, and safety. Run continuous LLM-as-Judge evaluation on production tracesWrite clean, maintainable Python; participate in code reviews; contribute to shared AI platform librariesOSS Integration & Data Engineering
Implement REST, NETCONF/YANG, SNMP trap ingestion, and gNMI streaming telemetry integrations connecting agents to NMS and EMS systemsBuild ServiceNow integrations for ticket read/write, triage updates, change record queries, and human-in-the-loop approval workflow triggers for the Execution AgentBuild the alarm and telemetry data normalisation pipeline converting multi-vendor OSS data into agent-consumable schemasImplement Kafka or equivalent event streaming consumers delivering real-time alarm data to the Alarm Correlation and Ticket Triaging agentsWork with data and integration engineers to normalise multi-vendor, multi-format network telemetry into consistent schemas the agents can reason overSafety, Guardrails & Risk
Implement guardrail architectures: hard limits, soft limits with human confirmation flows, blast radius controls, and escalation logicAssist the AI Solution Architect to assess blast radius for each agent — documenting worst-case impacts and designing specific mitigating controlsImplement and validate rollback procedures for all agent-initiated network actions, including automated rollback triggers based on post-execution KPI degradationWork with QA engineers to design and test solutions via defined test cases, and review required improvementsEnsure all agent architectures comply with IMDA regulatory requirements, AIVerify framework requirements, InfoSec policies, and CMB change governance frameworksObservability & Evaluation
Implement the Decision Audit Trail schema for all agents ensuring every decision is fully traceable, explainable, and available for post-incident reviewBuild the Agent Operations Dashboard for the NOC team: real-time agent status, decision volumes, accuracy metrics, and exception alertsDefine and implement the evaluation framework: factual, reasoning, tool-call, retrieval and planning accuracy, confidence thresholds, and human feedback captureImplement continuous evaluation of production agent traces using LLM-as-Judge for quality and safety; design human evaluation sample processBuild drift detection mechanisms that alert the team when agent output quality degrades before it becomes an operational incidentContainerise and deploy agent services using Docker and CI/CD pipelines; manage staging and production deployments with rollback capability The ideal candidate should possess:
Minimum 3 years of AI/ML engineering experience, with at least 1 year in production Agentic AI systems (not PoC or prototype-only)Demonstrable experience building AI agents that call external tools, manage state, and operate in production environments with real operational consequencesHands-on experience with LLM APIs (OpenAI, Anthropic Claude) or Open Source LLMs on vLLM (Qwen, Mistral, DeepSeek) in production — including prompt engineering, evaluation, and cost managementExperience building RAG pipelines with vector databases (Qdrant, Milvus, Pinecone, Weaviate, pgvector) in production, including hybrid search and rerankingPractical experience with at least one agentic AI framework: LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or custom tool-callingStrong Python — modular, testable, production-quality code. Proficiency with Git, CI/CD, Docker, and LLMOps practicesFull-stack awareness: REST APIs, front-end integration, data pipelinesDegree in Computer Science, Electrical Engineering, AI/ML, or related technical fieldHighly Desirable
Experience with Telco, utilities, or other 24×7 critical infrastructure environments where AI system failures have direct operational consequencesFamiliarity with OSS systems: NMS, EMS, network alarm management, NETCONF/YANG, or gNMI streaming telemetryExperience with event streaming platforms: Apache Kafka, Pulsar, or equivalentExperience integrating with ServiceNow REST API for ITSM dataExperience with AI observability tools: Langfuse, Braintrust, LangSmith, Weights & Biases, Prometheus/GrafanaExperience implementing AI systems subject to regulatory or formal risk governance frameworks (CMB, InfoSec review, audit requirements)Familiarity with network automation platforms (Cisco NSO, Nokia CloudBand, ONAP) as agent integration targetsFamiliarity with TM Forum frameworks including the Autonomous Network Maturity Model (L0–L5)Cloud ML platform experience: AWS SageMaker, Azure ML, or Google Vertex AIQualifications & Certifications
Required: Degree in Computer Science, Electrical Engineering, AI/ML, or related technical fieldDesirable: Professional certifications in Agentic AI development and architecting Why Join NCS
Lead high-impact AI management consulting 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.
We are driven by our AEIOU beliefs—Adventure, Excellence, Integrity, Ownership, and Unity—and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.
Together, we make the extraordinary happen.
Learn more about us at ncs.co and visit our LinkedIn career site.
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