18 days ago
Singapore, SingaporeStaff+
Responsibilities
- Own AI solution delivery from problem framing and feasibility through architecture, implementation, production release, and continuous improvement.
- Design enterprise architectures integrating AI capabilities with applications, APIs, data platforms, identity, security, and operational controls.
- Develop or review critical software components and establish coding, testing, quality, cost, and maintainability standards.
- Build production agentic applications using retrieval-augmented generation, MCP, function and tool calling, structured outputs, and multi-agent workflows.
- Design inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability, and cost optimization.
- Define measurable evaluation criteria, test sets, feedback loops, and monitoring for accuracy, reliability, safety, latency, cost, and business impact.
- Implement responsible AI guardrails, human oversight, access controls, privacy protections, and auditability with cross-functional partners.
- Collaborate with product owners, business leaders, architects, data specialists, and delivery teams on technical roadmaps.
- Mentor engineers, create reusable patterns and reference implementations, and communicate recommendations to technical and non-technical stakeholders.
Requirements
- Typically 10–12 years of professional experience in software engineering, solution architecture, platform engineering, or related enterprise technology roles.
- Strong record delivering production enterprise applications, integrations, or digital platforms in complex, regulated, or security-conscious environments.
- Recent hands-on experience with AI-enabled solutions such as agentic applications, retrieval-augmented generation, intelligent workflow automation, or machine-learning services.
- Strong software engineering fundamentals, including API design, distributed systems, automated testing, version control, CI/CD, observability, and secure development practices.
- Proficiency in Python and practical experience with at least one enterprise stack such as Java, .NET, or TypeScript/Node.js.
- Experience delivering on at least one major cloud platform, with depth in AWS, Microsoft Azure, or Google Cloud preferred over superficial multi-cloud coverage.
- Working knowledge of enterprise data integration, SQL, search/retrieval, and structured and unstructured information.
- Understanding of model and application evaluation, prompt and context design, privacy, security, responsible AI controls, and production monitoring.
- Experience leading technical work across multidisciplinary teams, mentoring engineers, and influencing architecture or engineering standards without relying solely on formal authority.
- Clear communication, commercial judgment, and ability to translate ambiguous business needs into feasible technical approaches and delivery plans.
- Preferred experience includes consulting or client-facing technology delivery, regulated industries, enterprise risk and governance, AI application frameworks or model platforms, and Kubernetes or infrastructure-as-code collaboration.
- A degree in computer science, engineering, or a related discipline, or equivalent professional experience.
Benefits
- Hybrid work arrangement with remote flexibility and an expectation to work from the local office or onsite with clients at least three days per week.
- Office-based teams designate at least one weekly anchor day for in-person collaboration.
- Diverse, inclusive, and flexible work environment with opportunities for collaboration, connections, and professional development.
Tech Stack
Categories
About Marsh
Marsh is a global insurance broker and risk advisor that helps businesses, public entities, and individuals assess, transfer, and manage risk through insurance placement, captives, and advisory services. It sells brokerage, risk consulting, and claims management across industries, including cyber and property, and operates in more than 130 countries. Marsh is a business of Marsh McLennan and is headquartered in New York.