At a Glance
- Tasks: Create AI solutions that transform investment workflows and enhance client experiences.
- Company: Join Barings, a leading firm committed to innovation and integrity.
- Benefits: Enjoy competitive pay, professional growth, and a supportive work culture.
- Other info: Dynamic role with opportunities for autonomy and career advancement.
- Why this job: Be at the forefront of AI technology, making a real impact in finance.
- Qualifications: Experience in software engineering and AI tools is essential.
The predicted salary is between 72000 - 88000 £ per year.
At Barings, we are as invested in our associates as we are in our clients. We recognise those who work diligently for us and reward them for personal and professional integrity, communication skills, distinct competencies and expertise in specific strategies, ability to collaborate as a team member and true dedication to the interests of our clients.
Barings is scaling the safe, governed adoption of AI across the firm, and the Innovation & Data Insights team within the Global Technology Division sits at the centre of that effort — pairing deep asset-management business domain knowledge with hands-on engineering to turn emerging AI capability into working solutions. We are seeking a Forward Deployed AI Engineer to embed directly with our Investment, Client & Support teams, to understand their workflows first-hand, and build AI-powered solutions that deliver measurable and tangible value.
This is a hands-on, delivery-focused role. You will scope and prototype rapidly, validate with the business, and ship production-grade solutions spanning automation, workflow orchestration, and client-facing tooling — using AI-native tooling across the entire lifecycle, from design and testing through to documentation. You will build on platforms such as Microsoft (Copilot, Cowork, Studio, Foundry) then work with engineering and the broader AI platform team to generalise what you learn into reusable platform capabilities.
The successful candidate combines strong business understanding across asset management with genuine software-engineering depth and daily fluency in AI-native development tools. You will be equally comfortable distilling an ambiguous business problem, writing production code, and teaching a team to use AI effectively and responsibly.
The Opportunity
- Apply cutting-edge AI to complex professional settings and real investment workflows, developing deep expertise with leading LLMs.
- Build intimate domain expertise in how our users work — from credit agreements to lease documents — so that solutions fit the real workflow.
- Become a core, trusted AI advisor to our stakeholders, driving adoption, value, and growth.
- Optimise processes for scale by defining and continually enhancing the internal workflows that shape and improve how we work.
- Own problems in ambiguity, operating with autonomy in fast-moving, unstructured environments — quickly distilling complex problems, learning on the fly, and driving to actionable solutions across customer and product needs.
Key Responsibilities
- Solution design & delivery
- Understand the business problem first, then leverage AI tools to accelerate solution design, building analytics and modelling solutions grounded in domain expertise.
- Partner with Business stakeholders, and architects to design, prototype, and deliver AI-powered solutions spanning automation, workflow orchestration, and client-facing tooling.
- Run tasks end-to-end, from scoping and prototyping through to deployment, using AI-native tooling throughout — not just for coding, but across design, testing, and documentation.
- Write production code that deploys through our pipelines and meets our engineering standards.
- Build custom integrations, workflow automations, and domain-specific solutions on top of Barings AI platform, including connectors to business data sources and document management systems.
- Prototype fast, validate with the business, iterate, and ship.
- Forward-deployed engagement
- Own the technical relationship with the business team throughout each engagement.
- Support the delivery of investment, client & operational workflows, identify high-value AI use cases, and build proofs of concept that demonstrate measurable impact.
- Return from engagements and work with engineering and product to generalise reusable patterns into platform capabilities.
- Participate in architecture discussions alongside core engineering.
- Enablement & training
- Deliver hands-on training, office hours, demos, and documentation that teach effective and responsible use of AI tooling — including prompting practices, workflow integration, and limitations.
- Platform contribution & feedback loop
- Build and contribute to AI platform architecture standards, including prompt-engineering patterns, agentic workflow design, and LLM integration guidelines.
- Collaborate with the wider technology and AI Platform teams to specify the dependencies analytical solutions require, such as data, development environments, and tooling.
- Collect, structure, and synthesise user feedback, pain points, and feature requests, translating them into clear requirements and prioritised recommendations for the AI Platform team.
- Identify patterns across teams to surface high-impact opportunities, quantify potential impact, and highlight use cases with broader applicability across the wider AI organisation.
- Responsible AI, risk & control
- Champion responsible AI usage, ensuring deployments adhere to firm policies on data security, model governance, and compliance.
- Demonstrate conformance to all Barings Enterprise Risk Management policies.
- Ensure all development activities are undertaken within the defined control environment.
Required Skills & Experience
- Software engineering experience with demonstrable, recent use of AI-native development tools as a core part of your daily workflow.
- Daily proficiency with AI coding tools such as Claude or GitHub Copilot.
- Hands-on LLM integration experience.
- Working knowledge of MCP (Model Context Protocol), REST APIs, and microservices architecture.
- Cloud platform experience.
- Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or similar.
- Strong analytical skills — the ability to understand a business problem first, then apply AI tools to accelerate solution design.
- Strong business understanding across asset management, with relevant domain expertise across investments, operations, data, and workflows.
- Initiative and ownership, with a track record of running tasks end-to-end with autonomy.
Preferred Qualifications
- Experience with external market providers such as Hebbia or comparable enterprise AI intelligence and agentic research platforms.
- Experience with Microsoft 365 Copilot, Copilot Cowork, and Copilot Studio.
- Familiarity with prompt-engineering patterns and agentic workflow design.
- Experience building connectors to document management systems and enterprise data sources.
- Experience delivering enablement — training, office hours, and documentation — to non-technical audiences.
Industry Experience (Preferred)
- Experience within asset management, financial services, or another regulated industry is strongly preferred. Familiarity with investment, operations, and data workflows — and with the documents that underpin them, such as credit agreements and lease documents — will help you build credibility and deliver value quickly.
Requisite Skills
Additional Skills
Barings is an Equal Employment Opportunity employer; Minority/Female/Age/Sexual Orientation/Gender Identity/Individual with Disability/Protected Veteran. We welcome all persons to apply.
Location: London, United Kingdom
Type: Full time
Forward Deployed AI Engineer in London employer: Baring Asset Management
At Barings, we pride ourselves on fostering a supportive and inclusive work environment where associates are valued for their contributions and encouraged to grow professionally. Located in the vibrant city of London, our team enjoys access to a wealth of resources and networking opportunities within the financial services sector, alongside competitive benefits and a commitment to work-life balance. Join us to be part of a dynamic culture that prioritises collaboration, innovation, and personal development.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed AI Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Baring Asset Management or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Explore Job Boards Specifically for Tech Roles
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We think you need these skills to ace Forward Deployed AI Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Baring Asset Management.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Baring Asset Management and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Baring Asset Management
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Baring Asset Management uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.