AI Specialist

Job description

Job Description Who we are Do you want to join our Geo-data revolution? Fugro’s global reach and unique know-how will put the world at your fingertips. Our love of exploration and technical expertise help us to provide our clients with invaluable insights. We source and make sense of the most relevant Geo-data for their needs, so they can design, build and operate their assets more safely, sustainably and efficiently. But we’re always looking for new talent to take the next step with us. For bright minds who enjoy meaningful work and want to push our pioneering spirit further. For individuals who can take the initiative but work well within a team. Job Summary: The AI Specialist (AI/ML Engineer) builds, deploys and supports AI, machine learning and automation solutions that translate approved designs into production-ready capabilities. The role prototypes rapidly, integrates AI into enterprise systems and owns the full delivery lifecycle (build, test, deploy, monitor), optimising for quality, safety, cost and reliability. This is a 3-year fixed term contract for placement in Singapore, and only open to SG/PR candidates. Key Responsibilities: 1. Solution Development & Deployment Build and deploy machine learning and LLM-powered applications, agentic workflows and automation pipelines. Develop rapid prototypes to validate use cases before full build investment. Integrate AI capabilities into enterprise systems via APIs and middleware. Convert validated prototypes into maintainable, production-ready components, services or applications. Own the full development lifecycle for assigned solutions (design, build, test, deploy, monitor). 2. Machine Learning Engineering & MLOps Develop, test, deploy and support machine learning models for approved business and technical use cases. Apply MLOps practices including model versioning, experiment tracking, deployment, monitoring and retraining. Support feature engineering, model validation and performance testing using appropriate datasets and metrics. Monitor model performance, reliability and drift, escalating risks or improvement needs where required. Document model assumptions, limitations, evaluation results and operational requirements. 3. LLM & Agentic Engineering Implement prompt engineering strategies and orchestration workflows. Build Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge bases and document stores. Implement tool use/function calling and orchestration frameworks as per approved standards. Evaluate and benchmark model outputs for accuracy, safety and business relevance. 4. Automation & Integration Build intelligent automation workflows connecting AI models to enterprise platforms (ERP, CRM, ITSM). Develop APIs and microservices that expose AI capabilities to internal applications. Implement monitoring, logging and alerting for deployed AI solutions. Optimise solutions for latency, cost and reliability in production environments. 5. Collaboration & Documentation Work with the AI Architect to build within agreed standards and patterns. Partner with data engineering on data inputs and evaluation sets. Support enablement sessions with demos and documentation. Document solutions for maintainability and knowledge transfer. Share reusable components, lessons learned and technical documentation to support alignment across APAC and wider enterprise teams. Requirements: Education: Tertiary institution/ bachelor’s degree (IT, Computer Science, Engineering, Data/AI, or equivalent experience) Working experience: 3-5 years Experience in software engineering with at least 2 years focused on AI/ML or LLM application development Strong Python proficiency — FastAPI, async programming, data manipulation Hands-on experience with LLM frameworks: LangChain, LlamaIndex Experience building and deploying RAG systems and vector database integrations API development and enterprise system integration experience Experience with agentic frameworks: AutoGen, CrewAI, LangGraph Familiarity with multiple frontier model APIs (OpenAI, Anthropic, Google, open-source via HuggingFace) Exposure to ML model training, MLOps practices and fine-tuning workflows Technical skills: includes Copilot 365, Copilot Studio, Github Copilot Management experience: 0-1 years Exposure to collaborative projects and agile delivery. AI & IT expertise: Proven experience contributing to AI, data-driven platform, automation or IT transformation initiatives through hands-on technical design, engineering, implementation and support. How to apply: Please include your latest resume in the application. We regret to inform this position is open only to SG/PR We regret to inform that we will only process applications made via our Careers website (and other linked portals) and only shortlisted applicants will be contacted. Disclaimer for recruitment agencies: Fugro does not accept any unsolicited applications from recruitment agencies. Acquisition to Fugro Recruitment or any Fugro employee is not appreciated .