At Barings, we are as invested in our associates as we are in our clients. We recognize 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.

We thank you for your interest in joining the Barings team, and invite you to explore our current employment opportunities.

Job Title: Forward Deployed AI Engineer

Business Title: Senior Associate

Department: Global Technology - Innovation & Data Insights

Location: London, UK

Role Summary

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 generalize 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.Expe