About this role
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 handoverDesign and build advanced agentic AI solutions including multi-agent systems, RAG pipelines with AI memory, planning and reasoning loops, and reflection patternsArchitect 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 paradigmsDesign, build, and deploy end-to-end ML models (classification, regression, time-series, NLP) and integrate them into production systemsDevelop GenAI applications including RAG pipelines, prompt-engineered chatbots, and lightweight agentic workflows using frameworks such as LangChain, LlamaIndex, LangGraph, or plain PythonImplement effective RAG architectures including chunking strategies, embedding selection, vector store configuration (Qdrant, Milvus, pgvector), and retrieval evaluationBuild 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 velocityWrite clean, maintainable Python code; participate in code reviews; contribute to shared libraries and internal AI platform componentsDesign 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 interactionsLead or co-facilitate client workshops including requirements discovery, solution walkthroughs, sprint demos, and retrospectivesTranslate ambiguous client requirements into well-defined technical user stories and acceptance criteriaCommunicate technical trade-offs and design decisions in clear, accessible language appropriate for business stakeholdersManage 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 practicesMentor junior AI engineers on both technical skills and professional conduct in client settingsContribute to internal knowledge-sharing through technical guidelines, lunch-and-learns, and building reusable AI platform components
The Ideal Candidate Should Possess:
Required Experience & Background
5–8 years of hands-on AI/ML engineering or data science experience, with at least 2–3 years in client-facing or technical-lead rolesProven delivery of complex AI projects end-to-end in a professional services, consulting, or systems integration environmentDemonstrable agentic AI project experience with systems incorporating RAG, AI memory, reflection, planning, and/or reasoning patternsCore Technical Competencies
Strong Python programming with Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow; comfortable writing modular, testable codeSolid understanding of ML fundamentals including feature engineering, model evaluation, bias-variance trade-off, and hyperparameter optimisationHands-on GenAI experience building RAG chatbots and applications, working with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or equivalent)Familiarity with vector databases and embedding models for semantic search and retrieval (e.g., Qdrant, Milvus, pgvector)Experience with at least one cloud platform (AWS, Azure, or GCP) for model training or deploymentProficiency with Git, CI/CD, and containerisation (Docker); familiarity with MLOps practicesProficiency in at least one additional programming language beyond Python (e.g., TypeScript/JavaScript, Java, Go, or advanced SQL)Deep hands-on experience with agentic frameworks such as LangGraph, CrewAI, AutoGen, or OpenAI Agents SDKExperience with LLM observability, evaluation, and guardrails tooling in production environmentsComfort with multiple programming languages and full-stack awareness (APIs, front-end integration, data pipelines)Working knowledge of MLOps and AI infrastructure including model serving, monitoring, and CI/CD for AI systemsClient Engagement & Communication Skills
Proven experience engaging directly with client stakeholders — including non-technical business owners — on AI solution design and deliveryStrong written and verbal communication skills; able to produce client-ready documentation, presentations, and technical specificationsExperience managing small delivery teams and coordinating across cross-functional groupsPreferred Qualifications (Nice-to-Have)
Experience building voice AI bots using a pro-code approach (Amazon Connect, Twilio, Deepgram, Whisper / ElevenLabs + custom orchestration, or LiveKit) — a strong differentiator for this roleExperience with MCP (Model Context Protocol) for tool integration in enterprise agentic systemsFamiliarity with responsible AI frameworks such as NIST AI RMF, MAS TRM, or equivalent governance standardsExposure to red-teaming and AI safety testing (OWASP LLM Top 10, promptfoo, adversarial prompt evaluation)Presales support experience including contributing to proposals, RFP responses, or solution scopingDomain experience in government, financial services, telco, or e-commerce AI use casesAWS, Azure, or GCP certifications (ML or AI specialty) are preferred but not mandatoryEducation Qualification
Degree in Statistics, Computer Science, Engineering, Data Science, or equivalent quantitative discipline
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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