About this role
As a Platform AI Engineer, you will be a hands-on contributor within the AI Center of Excellence (AI COE), a centralized platform product team that builds and operates enterprise-grade AI and data platforms. Your focus is on developing shared, production-ready AI capabilities – such as LLM services, workflows, and platform integrations – that enable internal engineering teams to safely, reliably, and efficiently consume AI at scale.
What will you do?
AI Platform Engineering
Build and enhance AI platform services using Python and cloud-native technologiesImplement AI workflows including RAG pipelines, inference services, and agent-based logicDesign AI services with production-grade considerations such as latency, throughput, resilience, and cost efficiencyPlatform Integration
Integrate AI services with model platforms, AI gateways, vector databases, and inference runtimesIntegrate with data pipelines (batch and streaming) to support AI workflowsWork with observability and LLMOps tooling to enable monitoring and operational visibilityReliability, Deployment & Operations
Collaborate with platform engineers on deployment, scaling, and reliability in containerized / Kubernetes environmentsParticipate in production support, incident resolution, and continuous improvementBalance rapid experimentation with enterprise requirements such as security, governance, and complianceDeveloper Enablement
Contribute to shared libraries, SDKs, and internal developer toolingImprove platform usability and overall developer experienceParticipate in code reviews, testing, and Git-based CI/CD workflows
The ideal candidate should possess:
Strong hands-on experience building backend or platform services using Python3–5 years of professional software engineering experience, including work on shared or platform services1–2 years of hands-on experience with AI, ML, or LLM-based systems in production or pre-production environmentsExperience with LLM integration patterns, including prompt engineering and RAG workflowsExperience with vector databases (e.g. Milvus) and embedding-based retrievalUnderstanding of model serving and inference runtimes (e.g. vLLM or equivalent)Familiarity with AI gateways and access control patterns for LLMsExperience integrating with data pipelines (batch and streaming)Basic understanding of LLMOps and observability concepts for AI systemsExperience working in containerized and Kubernetes-based environmentsFamiliarity with Git-based workflows and CI/CD pipelinesStrong ownership mindset, collaborative approach, and willingness to learn evolving AI technologies
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.
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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