Generative AI Engineer

We’re looking for a Forward Deployed AI Engineer to join a fast-growing AI consultancy working with leading organisations in areas such as capital markets and investment management. You will work directly with clients to design, build, and deliver production-grade AI systems, embedding into complex environments to solve real operational and data challenges. This role blends software engineering, AI system design, and client delivery, with a strong focus on scalable, production-ready solutions.

What you’ll be doing:

• Build and evolve AI-driven origination and workflow platforms, including deal intake, pipeline management, relationship intelligence, approvals, and execution processes.
• Design and implement microservices and APIs that integrate data across enterprise systems such as CRMs, internal platforms, and external data providers.
• Translate complex financial and operational logic — including pipeline structures, attribution models, allocations, and reporting frameworks — into scalable technical systems.
• Architect and optimise data models and database layers, including schema design, indexing strategies, query tuning, and stored procedures.
• Develop and maintain CI/CD pipelines and engineering tooling to support reliable, frequent, and high-quality deployments.
• Implement event-driven architectures using Kafka, enabling real-time data processing, system decoupling, and auditability.
• Ensure high performance, reliability, and scalability across distributed systems, including observability, monitoring, and production readiness.
• Partner with product, operations, and investment stakeholders to refine requirements and deliver iterative solutions in Agile environments.

Core requirements:

• 8+ years of hands-on software engineering experience across Python and object-oriented languages (Java or C++).
• Strong background delivering production-grade full-stack or backend systems.
• Deep understanding of cloud architecture (AWS, Azure, or GCP) with a focus on scalable and secure systems.
• Strong proficiency in Python and SQL, plus experience with either Java or .NET.
• Solid DevOps experience including Git, CI/CD pipelines, and containerisation (Docker, Jenkins or equivalent tools).
• Proven experience designing and building microservices-based architectures in distributed systems.
• Advanced knowledge of database systems, including schema design, performance tuning, and query optimisation.
• Experience working with event-driven architectures and messaging systems such as Kafka.
• Familiarity with both NoSQL and NewSQL databases, including trade-offs and use cases.
• Ability to take ambiguous business requirements and turn them into clear technical designs and working systems.

AI Engineering capability (essential):

• All engineers in this team are expected to meaningfully apply AI in production systems, including:
• Building and deploying LLM-based applications in production environments.
• Designing agentic workflows and multi-step AI systems.
• Implementing RAG (Retrieval-Augmented Generation) pipelines.
• Working with OpenAI or Anthropic APIs.
• Using vector databases and embedding-based search systems.
• Applying prompt engineering techniques effectively.
• Building AI evaluation, monitoring, and observability frameworks.
• Understanding ML fundamentals where relevant (embeddings, fine-tuning, context engineering).

Additional note:

The business is also interested in speaking with UK-based engineers for internal platform and AI product engineering roles. If you are more interested in building internal systems rather than client-facing delivery, you are still encouraged to apply.