Lead AI Engineer
Willis Towers Watson3 days ago
Base Salary
$100k - $350k/yr
Responsibilities
- Work as a forward deployed engineer with brokers, actuaries, catastrophe modellers, clients, and delivery teams to build high-value AI solutions.
- Prototype working software rapidly and carry successful ideas through code review, delivery, testing, release, and production handover.
- Design and build reusable agentic analytics and AI-enabled products using large language models, RAG, MCP, and agent frameworks.
- Own production AI quality through evaluation, testing, guardrails, observability, security, and cost management.
- Apply quantitative reasoning and insurance, exposure, loss, and catastrophe-modeling knowledge to risk-data solutions.
- Shape AI technical direction with Delivery Leads, Product Leads, Product Architects, actuaries, and engineers.
- Use and critically review AI coding assistants and agentic workflows, including human- and AI-generated code.
- Mentor colleagues informally, share knowledge, and evaluate emerging AI models, tools, and techniques.
Requirements
- 10+ years of professional software engineering experience with a record of leading complex delivery as a hands-on technical authority.
- At least 2 years of recent hands-on experience building and shipping LLM-based and agentic systems to production using RAG, prompt engineering, and agent orchestration.
- Expert hands-on use of AI coding assistants and agentic development tools, with the ability to validate and secure their output.
- Strong Python skills and proficiency in at least one of C#/.NET or TypeScript with Angular and/or React.
- Commercial cloud experience, preferably Azure, plus experience with GitHub or Azure DevOps and software delivery practices.
- Strong analytical and quantitative background in mathematics, statistics, engineering, computer science, or a related discipline.
- Strong knowledge of insurance, reinsurance, risk analytics, actuarial work, or catastrophe modeling, or the ability to become expert quickly in a complex quantitative field.
- Ability to work directly with business users or clients, create working demos quickly, move concepts into production, and communicate technical trade-offs to senior stakeholders.
- Experience evaluating recent AI tools, models, and techniques hands-on and making informed adoption decisions.
- Preferred qualifications include multi-agent workflows, reusable MCP servers or tools, regulated-environment AI operations, model governance, responsible AI, microservices, containerization, geospatial or financial-modeling data, mathematical algorithms, applied machine learning, statistics, data science, and AI engineering community contributions.
- Degree-level qualification in a quantitative discipline is required; postgraduate study is valued.
Benefits
- Hybrid working with regular office attendance for meetings and workshops, occasional stakeholder travel, medical/dental/vision coverage, health and dependent-care accounts, insurance and wellbeing programs, paid holidays and leave, short- and long-term disability, a contributory pension and 401(k) savings plan, and potential deferred compensation eligibility for sufficiently senior roles.
Tech Stack
Categories
Forward Deployed
About Willis Towers Watson
WTW is a global advisory, broking, and software firm serving employers, insurers, and institutional clients across people, risk, and capital. It provides insurance brokerage and risk advisory, employee benefits and pensions consulting, and HR/benefits administration software and analytics. Headquartered in London and listed on NASDAQ (WTW), the company was formed in 2016 via the Willis Group–Towers Watson merger and operates in roughly 140 markets worldwide.