> Markdown version of [/jobs/ext/3866296-forward-deployed-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3866296-forward-deployed-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward-Deployed AI Engineer - **Company:** UBS - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $115,000.0 - $137,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Copilot Studio, Low-code - **Published:** October 22, 2026 - **Apply:** https://jobs.ubs.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=25008&siteid=5012&PageType=JobDetails&jobid=352843 ## About the Role * Financial markets exposure. At least two years of financial-services experience, ideally within Global Markets sales, trading or a closely related front-office environment. * Real curiosity about AI. You actively use today's AI tools and have a practical understanding of where they are powerful, where they fail, and where human judgement still matters. * Hands-on building ability. Experience with AI and low-code tooling such as Cowork, Copilot Studio or similar platforms, plus the appetite to master the next tool just as quickly. * A process engineer's mindset. You can take a workflow apart, identify its constraints and inefficiencies, and redesign it rather than simply automating the existing mess. * Strong communication skills. You can earn the trust of busy front-office professionals, ask incisive questions and explain technology without hiding behind jargon. * Exceptional learning velocity. A new desk, asset class, dataset or tool should take you days to begin understanding, not months. * Technical fluency. You are comfortable working with data, understanding system interactions, scoping an API and building a working prototype. Deep software-engineering experience is welcome, but it is not the purpose of the role. * Commercial judgement. You can distinguish an interesting problem from a valuable one, prioritise ruthlessly, and say no or redirect work when that is the right answer. You are * Practical, focused and biased toward action. * Comfortable operating on a busy trading floor and communicating with people at every level. * Curious about how the business works, not simply about the technology. * A fast learner who is comfortable with ambiguity and incomplete information. * Able to work independently while thriving in a highly collaborative environment. * Comfortable balancing speed and innovation with the governance standards of a regulated institution. * Motivated by seeing something you built change how people actually work. ## Description Turn front-office problems into governed, production-grade AI solutions that transform sales workflows. You will own the journey from discovery through implementation: understand how work actually happens, identify where AI can materially improve it, rapidly put solutions in front of users, and partner with senior Global Markets quants and technology teams on governance, productionisation and scale. This is a role for someone who likes interpreting and doing, not consulting and enabling from the sidelines. What you will do * Embed with Distribution desks. Understand how work actually happens, map workflows end to end, identify friction and waste, and prioritise opportunities against the seven pillars of the Global Markets Sales strategy. * Build quickly. Use the bank's existing AI and low-code capabilities to automate workflows and get useful solutions in front of users in days rather than months. The objective is not to build bespoke software where an existing tool can solve the problem. * Redesign before you automate. Challenge unnecessary steps, hand-offs and duplication rather than simply using AI to automate an inefficient process. * Own the dependencies. Identify the APIs, data and entitlements required for your solutions, specify what is needed clearly, and drive those requirements through to delivery. * Design for compliant AI. Understand the architectural and governance considerations around AI systems and ensure solutions operate within the bank's AI, data, risk and control frameworks. * Unlock the right data. Recommend how each desk should organise and access its information to enable AI use cases while adhering to the bank's need-to-know framework. * Know what not to build. Solve problems directly where the available tools allow it. Where a requirement genuinely needs strategic engineering, route it to Quant or Technology with a well-defined problem statement, requirements and expected business outcome. * Drive adoption, not just delivery. Train users, observe how solutions perform in real workflows, iterate quickly, spread successful patterns across desks, and make sure what you build is still being used a month later. * Scale what works. Spot recurring problems across products, regions and desks and turn successful local solutions into reusable capabilities. Your Career Comeback We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback. The team This role sits at the intersection of Global Markets Distribution, Quantitative Engineering and regional Sales, with connectivity to the senior leaders responsible for each. It is an embedded, front-office role. Success is measured not by recommendations or prototypes alone, but by whether better ways of working make it into the hands of users and stay there.