Forward Deployed AI Engineer
Willis Towers Watson1 day ago
London, United KingdomStaff+
Responsibilities
- Design and build AI-enabled applications, copilots, agents, extraction pipelines, prediction interfaces, and decision-support tools.
- Work directly with business teams, product owners, clients, and operational users to translate workflows and constraints into technical solutions.
- Build and tune LLM workflows, prompt strategies, schema-driven extraction, tool-calling patterns, agent orchestration, evaluation loops, and human-in-the-loop controls.
- Integrate AI solutions with enterprise systems, APIs, data platforms, document repositories, workflow tools, observability platforms, and identity and access management services.
- Engineer production solutions for reliability, scalability, latency, maintainability, cost control, logging, monitoring, and operational support.
- Create evaluation datasets, test harnesses, validation tools, regression checks, and quality review workflows.
- Define solution architecture, engineering standards, reusable patterns, and implementation approaches for AI platforms and services.
- Prepare structured and unstructured data, improve metadata, design retrieval strategies, and identify knowledge gaps.
- Embed access controls, audit logging, data protection, responsible AI controls, security review, and compliance requirements.
- Support adoption through demonstrations, pilots, training, documentation, feedback loops, and iterative improvement.
- Mentor engineers, resolve production challenges, and lead technical delivery across teams.
Requirements
- Significant professional experience in software engineering, technical leadership, solutions architecture, or platform engineering, ideally in enterprise-scale environments.
- Experience delivering production applications using APIs, distributed systems, microservices, automated testing, CI/CD, observability, and cloud platforms.
- Hands-on experience building and deploying agentic AI solutions using Anthropic Claude, including AI agents, tool orchestration, reasoning workflows, Model Context Protocol, and enterprise automation.
- Experience building AI-enabled systems such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction interfaces, or agentic workflows.
- Experience supporting business-critical systems where reliability, maintainability, operational support, and measurable business impact are essential.
- Experience collaborating with data scientists, product managers, QA teams, architects, security teams, and senior stakeholders.
- A track record of mentoring engineers, leading technical delivery, establishing engineering standards, and influencing teams beyond direct line management.
- Strong enterprise engineering experience with modern full-stack technologies including .NET, Azure, SQL, React, and Angular.
Benefits
- 25 days of annual leave plus an additional WTW day.
- Private healthcare, life insurance, group income protection, and regular health assessments.
- Defined contribution pension scheme with company-matched contributions up to 10%.
- Hybrid working with remote flexibility and occasional office collaboration.
- Employee assistance programme and a fully paid volunteer day.
- Optional electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and other perks.
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.