About the role

DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations. The Artificial Intelligence (AI) Engineer is a specialist role focused on the engineering, deployment, and scaling of advanced AI systems to drive the Bank’s digital and operational transformation. This position is responsible for building the robust technical foundations required for enterprise-grade applications, including Conversational AI agents, operations automation, and Generative AI initiatives. By developing high-performance pipelines and reusable components, you will ensure that AI products are reliable, compliant, and capable of delivering next-generation experiences for both customers and employees. As the AI Engineer with Deeplight, your responsibilities will include: - Building and scaling next-generation Conversational AI platforms (voice and chat) using LLM-based agents and multi-agent orchestration frameworks. - Developing automation agents for critical banking functions such as KYC, compliance, risk monitoring, and customer service. - Implementing Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases and knowledge graphs to power enterprise search. - Model Optimization: Design and refine prompts to optimize LLM performance and apply advanced parameter-efficient fine-tuning techniques. - Operationalizing embedding models and custom ML solutions by building APIs, SDKs, and CI/CD pipelines with automated retraining and drift management. - Establishing engineering standards for model fairness, security, explainability, and disaster recovery to ensure operational resilience. - Acting as an analytics translator, identifying opportunities for leveraging data to solve complex business problems across functional teams. As an AI consultancy, our greatest asset is the expertise of our people. While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight. We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills. You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders. If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in. Benefits Benefits & Growth Opportunities: - Competitive salary. - Visa Sponsorship for the successful individual. - Comprehensive health insurance for the successful individual. - Professional development and certification support. - Opportunity to work on cutting-edge AI projects. - Career advancement opportunities in a rapidly growing AI company. This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients. At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions. Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates. If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

Requirements

What we need from you:

- Bachelor’s degree in a quantitative field (Computer Science, AI, Software Engineering, or Mathematics); a Master’s degree in AI/ML is highly preferred.

- 5+ years in AI/ML engineering or large-scale digital product engineering, ideally within a major digital transformation or digital-only bank project.

- Proven experience deploying large-scale AI/ML solutions within a regulated environment (Banking or Financial Services preferred).

- Hands-on experience with MLOps tools (MLflow, CI/CD) and data visualization platforms (Tableau, Power BI)

- Expert-level programming in Python specifically for ML/AI engineering and Generative AI applications.

- Deep knowledge of transformer models, multimodal architectures, and agentic AI systems (multi-agent frameworks/human-in-the-loop).

- Expertise in vector databases (Pinecone, Weaviate, Milvus), knowledge graphs, and both SQL/NoSQL systems (Postgres, MongoDB).

- Proficiency in Azure AI Foundry or AWS SageMaker, including serverless deployments (Lambda/Azure Functions) and containerization (Docker, Kubernetes).

- Deep understanding of LLM evaluation metrics and observability frameworks for monitoring agentic workflows.

It would also be beneficial if you have experience of the following:

- Ability to quickly build and test AI prototypes while maintaining a focus on enterprise-grade security and compliance.

- Active engagement in the AI community with a track record of evaluating emerging tools like LangChain, CrewAI, and Bedrock.

- Exceptional communication skills to bridge the gap between technical requirements and business objectives for non-technical stakeholders.

- Deep understanding of emerging trends such as Reinforcement Learning from Human Feedback (RLHF) and multimodal AI.

Responsibilities

Building and scaling next-generation Conversational AI platforms (voice and chat) using LLM-based agents and multi-agent orchestration frameworks. Developing automation agents for critical banking functions such as KYC, compliance, risk monitoring, and customer service. Implementing Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases and knowledge graphs to power enterprise search. Model Optimization: Design and refine prompts to optimize LLM performance and apply advanced parameter-efficient fine-tuning techniques. Operationalizing embedding models and custom ML solutions by building APIs, SDKs, and CI/CD pipelines with automated retraining and drift management. Establishing engineering standards for model fairness, security, explainability, and disaster recovery to ensure operational resilience. Acting as an analytics translator, identifying opportunities for leveraging data to solve complex business problems across functional teams.

Skills

Python programming for ML/AI engineering

MLOps tools (MLflow, CI/CD)

data visualization platforms (Tableau, Power BI)

transformer models and multimodal architectures

agent-based systems and multi-agent frameworks

vector databases (Pinecone, Weaviate, Milvus)

knowledge graphs

SQL/NoSQL systems (Postgres, MongoDB)

Azure AI Foundry or AWS SageMaker

serverless deployments (Lambda/Azure Functions)

containerization (Docker, Kubernetes)

LLM evaluation metrics and observability for agentic workflows

Retrieval-Augmented Generation (RAG) pipelines

KYC, compliance, risk monitoring automation in banking

embedding models deployment and CI/CD with automated retraining

About the role

Requirements

Responsibilities

Skills

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