AI Engineer
Summary
Designs and deploys enterprise-grade AI/Generative AI solutions (LLMs, RAG) for a global financial services client, bridging architecture reviews, system integration, and production support.
- Work with one of the large financial services firms - be a part of global projects
- 6-12 Months contract with a potential to extend on a long-term basis
Role Summary
The role is responsible for designing, building, and deploying enterprise-grade AI and Generative AI solutions, including Large Language Model (LLM)-powered applications, Retrieval-Augmented Generation (RAG) systems, and AI-driven workflows. The successful candidate will be responsible for completing and refining solution designs, participating in architecture governance reviews, supporting solution delivery through deployment, and collaborating with cross-functional teams to deliver scalable and secure AI solutions.
Key Responsibilities
- Complete and refine end-to-end solution designs for AI and Generative AI initiatives.
- Participate in and present solution designs during architecture and governance review forums (e.g. GSRC, LSRC).
- Provide technical recommendations on where AI solutions would be more effective than Straight Through Processing (STP) and support key architectural decision-making.
- Design, build, and deploy enterprise-grade AI and Generative AI solutions.
- Develop LLM-powered applications, Retrieval-Augmented Generation (RAG) solutions, and agentic AI workflows.
- Integrate AI solutions with enterprise applications, APIs, and existing technology platforms.
- Collaborate with Product Owners, Data Engineers, Platform Engineers, Architects, and business stakeholders throughout the delivery lifecycle.
- Support System Integration Testing (SIT) and User Acceptance Testing (UAT), ensuring solutions meet business and technical requirements.
- Participate in Change Advisory Board (CAB) activities, release management, deployment planning, and production implementation.
- Support production deployment, monitoring, troubleshooting, and optimisation of AI solutions.
- Ensure solution designs align with enterprise architecture, security, governance, and compliance standards.
Required Skills & Experience
- Proven experience in AI, Machine Learning, Data Engineering, or Software Engineering.
- Strong Python programming skills.
- Hands-on experience with Generative AI technologies, Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG).
- Experience designing and developing enterprise AI applications.
- Familiarity with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- Strong understanding of software engineering principles, REST APIs, system integration, and application architecture.
- Experience supporting solution delivery across design, build, testing, deployment, and production support.
Preferred Skills
- Experience with vector databases.
- Knowledge of MLOps and LLMOps practices.
- Experience developing agentic AI solutions and AI orchestration frameworks.
- Experience working within enterprise or regulated environments.
- Experience participating in architecture governance and design review forums.
- Understanding of release management processes, including CAB and production deployment.