{"id":824131,"url":"https://alion.io/job/ncs-ai-architect","title":"AI Architect","company":{"id":8907,"name":"NCS","domain":"ncs.co","url":"https://alion.io/company/ncs-co","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":82,"open_postings":371,"ghost_share":0.296,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":83000,"max_usd":236000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AWQ","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"FinOps","optional":false},{"name":"GCP","optional":false},{"name":"GGUF","optional":false},{"name":"GPTQ","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LiveKit","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Milvus","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"Ollama","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"pgvector","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"TGI","optional":false},{"name":"Tool Use","optional":false},{"name":"vLLM","optional":false},{"name":"LangChain","optional":true},{"name":"PEFT","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-04-20T13:48:58Z","employer_posted_date":"2026-04-20","last_verified_at":"2026-10-16T20:56:33Z","board_verified":true,"closed_at":null,"days_open":179,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":178},"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.\n Role Overview\nThe Principal AI Architect is a senior technical leader responsible for the architectural integrity and strategic depth of NCS's most complex AI programmes. This is not a reference-architecture role - you go deep: design patterns, component-level trade-off analysis, cost modelling, and hands-on validation of the systems you design. You will engage with C-level and senior technical stakeholders on client side, shape multi-year AI platform roadmaps, and serve as the definitive technical authority across ML, GenAI, and agentic AI domains within NCS's AI practice.\nExperience with architecting and building AI voice bot from scratch using livekit or similar framework would be a big plus.\nKey Responsibilities\nArchitecture & Design\nOwn end-to-end technical architecture for large-scale AI programmes: from data ingestion and model training through inference infrastructure, agentic orchestration, and front-end integration.\nGo beyond reference architecture: produce detailed design pattern specifications, component interaction diagrams, data flow models, and failure mode analyses.\nMake and defend technically grounded design decisions: LLM selection and cost modelling, build-vs-buy analysis, open-weight vs. proprietary model trade-offs, and infrastructure sizing.\nDesign enterprise agentic AI systems incorporating multi-agent orchestration, RAG, AI memory, planning, reasoning, reflection, and tool integration via MCP or equivalent.\nSpecify AI governance and safety architectures: guardrails, observability stacks, responsible AI controls aligned to NIST AI RMF, MAS TRM, and applicable regulatory frameworks.\nDefine evaluation and quality frameworks across ML and GenAI: metrics selection, benchmark design, red-teaming protocols, and production monitoring strategies.\nLead architecture reviews; challenge and validate designs proposed by AI Engineers and Senior AI Engineers.\nTechnical Depth & Hands-On Contribution\nMaintain active hands-on capability: prototype critical components, validate architectural assumptions through working code, and lead proof-of-concept builds.\nDeep working knowledge of the full AI stack: data pipelines, feature stores, model training (classical ML + fine-tuning LLMs), inference optimisation (quantisation, distillation, batching), and agentic orchestration.\nEvaluate and select from the evolving AI tooling ecosystem - vector databases, agentic frameworks, LLM gateways, MLOps platforms, observability tools - with defensible rationale.\nDesign cost-optimised AI infrastructure: GPU/CPU sizing, quantisation strategies (GPTQ, AWQ, GGUF), cross-cloud connectivity, and FinOps for AI workloads.\nStakeholder Management & Delivery Leadership\nServe as the senior technical authority in client engagements: lead architecture workshops, executive briefings, and technical governance reviews.\nBuild trusted relationships with CTO, Head of AI, and senior engineering leaders on client side; navigate complex stakeholder dynamics across delivery programmes.\nDrive alignment between business objectives and technical architecture across multi-vendor, multi-workstream programmes.\nProvide architectural oversight and direction across delivery squads; escalate and resolve technical blockers at programme level.\nContribute to presales: lead solution architecture for major bids, produce technically credible and commercially sound proposals.\nDevelop and grow the AI engineering talent within the NCS AI practice; act as a technical mentor and role model across the team.\nThought Leadership & Practice Development\nDefine and evolve NCS's internal AI architecture standards, design pattern libraries, and reusable platform components.\nRepresent NCS externally: conference presentations, published thought leadership, and client advisory engagements.\nIdentify emerging technology trends and translate them into practice capability investments.\n Experience & Education\n10-15+ years of progressive experience in AI/ML engineering, data science, or software engineering, with at least 5 years in architecture or technical leadership roles.\nDegree in Computer Science, Engineering, Statistics, or equivalent; advanced degree (MSc/PhD) advantageous.\nProven track record designing and delivering large-scale AI programmes end-to-end - not just contributing to them.\nExperience building AI products or platforms from scratch, or serving as lead architect on enterprise AI programmes with significant complexity and scale.\nBackground in system integration, technical consultancy, or professional services - with direct accountability for architecture quality in client-facing engagements.\nTechnical Depth\nStrong Python programming at production grade: modular, testable, well-documented code across ML and GenAI application stacks.\nDeep ML fundamentals: feature engineering, model evaluation, classical ML algorithms, bias-variance trade-offs, and hyperparameter optimisation.\nExtensive hands-on GenAI experience: RAG pipelines, LLM API integration (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI), prompt engineering, and evaluation.\nExpert-level knowledge of vector databases and embedding architectures (Qdrant, Milvus, pgvector) for semantic search and retrieval at scale.\nDeep multi-cloud platform expertise (AWS, Azure, GCP) across AI/ML services, model training, and inference infrastructure.\nAdvanced containerisation and MLOps: Docker, Kubernetes, CI/CD pipelines for AI systems, model serving, and production monitoring.\nMulti-language programming proficiency; ability to read, reason about, and contribute to code across the full stack.\nDeep hands-on experience with agentic frameworks: LangGraph, CrewAI, AutoGen, OpenAI Agents SDK - at architectural depth, not just usage.\nExpert-level knowledge of agentic AI design patterns: multi-agent orchestration, memory architectures, planning and reasoning loops, reflection, and tool-use integration.\nDeep hands-on experience with GenAI infrastructure: LLM serving (vLLM, TGI, Ollama), fine-tuning (LoRA, QLoRA), model quantisation, and cross-cloud API architecture.\nDemonstrated ability to cost AI systems: TCO modelling, GPU/inference cost optimisation, build-vs-buy analysis across proprietary and open-weight LLMs.\nStrong command of responsible AI at architecture level: governance frameworks, safety controls, bias mitigation, auditability, and regulatory compliance.\nLeadership & Stakeholder Skills\nProven stakeholder management at senior levels: ability to advise, influence, and build confidence with client executives and technical leadership.\nExperience leading cross-functional, multi-vendor delivery programmes; comfortable operating in complex organisational environments.\nStrong written communication: ability to produce architecture documents, executive briefings, and technical proposals that are clear, precise, and persuasive.\n 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.\nTogether, we make the extraordinary happen.\nLearn more about us at ncs.co and visit our LinkedIn career site.\nScam Alert\nWe are aware of fraudulent job offers and impersonations of NCS recruiters. Phishing emails using convincing-looking but fake addresses are also commonly used to trick you into thinking that they come from official NCS sources.\nPlease note that all official communications from NCS Group will only be sent from verified corporate email addresses. Always check that the sender’s email address ends with the genuine NCS domain, @ncs.com.sg and beware of extra letters, symbols or misspellings. 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