ML Quant Strat

Detailed Job Description

Our client is a leading global financial institution undertaking a significant transformation in the application of artificial intelligence across its Investment Banking division. As part of this strategic initiative, they are expanding their Research AI team and are seeking a Staff Forward Deployed AI Engineer to drive the development of next-generation AI solutions that enhance how financial research is discovered, generated and distributed.

This is a highly visible role operating at the intersection of machine learning, large language models, software engineering and financial research. The successful candidate will work directly with research leadership, analysts, product teams and engineering groups to identify opportunities for AI adoption, rapidly prototype solutions and help shape the future AI strategy of the organisation.

Key Responsibilities

AI Innovation & Prototyping

• Design, prototype and validate AI-driven solutions for investment research workflows.
• Build proof-of-concepts leveraging machine learning, large language models, agentic AI and multi-agent systems.
• Define success metrics and demonstrate measurable business impact through AI applications.
• Support the integration of AI into research discovery, content generation and distribution processes.

Stakeholder Engagement

• Partner directly with research analysts, sector specialists and business leaders to identify opportunities for AI-driven improvements.
• Gather requirements from non-technical stakeholders and translate them into scalable technical solutions.
• Communicate complex technical concepts to senior decision-makers across research and investment banking functions.

Engineering & Architecture

• Develop robust proof-of-concept architectures that can be transitioned into enterprise production environments.
• Build and deploy solutions across AWS-based infrastructure and cloud-native environments.
• Integrate AI solutions with existing data platforms, research tooling and publication workflows.
• Apply strong engineering principles, observability practices and root-cause analysis across complex systems.

Cross-Functional Collaboration

• Partner closely with AI platform teams, software engineers, product managers and business stakeholders.
• Collaborate with groups supporting portfolio managers, traders and client-facing research activities.

Required Skills & Experience

• Extensive software engineering experience in Python, including object-oriented development and package management.
• Strong experience with a compiled language such as Java or C++.
• Deep understanding of AWS technologies including SageMaker, Bedrock, S3, Redshift, Neptune, EKS, EMR, Glue and Kinesis.
• Hands-on experience building AI/ML systems, LLM applications, agentic workflows and multi-agent architectures.
• Strong knowledge of machine learning system design and enterprise-scale deployments.
• Ability to engage effectively with both technical and non-technical stakeholders.
• Experience delivering technology solutions within large, complex and regulated environments.

Desirable Experience

• Exposure to financial markets, investment research or quantitative research environments.
• Understanding of Data Mesh and Data Product frameworks.
• Experience with agentic orchestration frameworks, MCP and advanced AI tooling.
• Cloud architecture, machine learning or data engineering certifications.
• Experience with Kubernetes, OpenShift, gRPC and modern cloud-native infrastructure.

Why Apply?

This opportunity offers the chance to work at the forefront of AI innovation within financial markets. You will play a key role in defining how advanced AI technologies are adopted across a major research organisation, working on high-impact initiatives that directly influence analysts, portfolio managers, traders and clients. The role combines cutting-edge technical challenges, senior stakeholder exposure and the opportunity to shape the future direction of AI within a globally recognised institution.