
AI Solution Specialist
Marsh & McLennan Companies2 hours ago
Singapore, SingaporeMid Level
Responsibilities
- Design and architect AI solutions for knowledge assistants, document intelligence, workflow automation, decision support, and predictive analytics.
- Write clean, maintainable, production-quality Python code using best practices and design patterns.
- Develop end-to-end AI pipelines covering data preprocessing, model development, prompt engineering, retrieval workflows, and API design.
- Partner with business, product, engineering, data, and architecture stakeholders to assess requirements and deliver AI-enabled solutions.
- Prototype, test, and refine AI models, prompts, and workflows for performance, reliability, and business value.
- Ensure AI solutions comply with security, privacy, governance, and responsible AI requirements.
Requirements
- At least 4 years of experience in AI/ML development, data science, or AI engineering.
- Hands-on experience deploying AI/ML solutions in production enterprise environments.
- Strong Python proficiency and proficiency in at least one additional language such as Java, TypeScript, Scala, or Go.
- Hands-on experience with generative AI and LLM-based applications, including prompt engineering, fine-tuning, and RAG.
- Familiarity with LLM ecosystems such as OpenAI, Hugging Face, or Anthropic and vector databases such as Pinecone, Weaviate, or Milvus.
- Experience using at least one cloud platform—AWS, Azure, or GCP—to deploy AI solutions.
- Understanding of enterprise security, data governance, and responsible AI principles.
- A master's degree or advanced certification in Machine Learning, AI, Data Science, or Computer Science is preferred.
- Experience in insurance, financial services, or another regulated industry is preferred.
- Familiarity with document processing, knowledge management, intelligent automation, or intelligent search is preferred.
- Experience with MLOps, multi-agent systems, or scaling AI solutions from prototype to production is preferred.
Benefits
- Professional development opportunities, interesting work, and supportive leaders.
- Inclusive and flexible work environment with opportunities to create solutions and have impact.
- Range of career opportunities, benefits, and rewards supporting employee well-being.
- Hybrid work arrangement requiring colleagues to work in their local office or onsite with clients at least three days per week; office-based teams identify at least one weekly anchor day.