Software Engineer - AI Focused

About the role

We are seeking a Software Engineer with a strong focus on AI to design, develop, and maintain large‑language‑model (LLM) powered applications that integrate with core banking systems. The role involves full‑stack development, architecture design, and ensuring production reliability while staying current with emerging Agentic technologies.

Key responsibilities

• Lead solution architecture and development of applications that integrate LLMs with banking core systems using patterns such as Agentic Orchestration, Multi‑Agent Systems, RAG, MCP integration, and Prompt Engineering.
• Develop front‑end web‑based user interfaces to expose Agentic applications to the workforce.
• Ensure reliability, usability, and responsiveness of deployed applications in the production environment.
• Engineer robust LLM evaluation frameworks, maintain accuracy standards, and implement controls to mitigate hallucinations.
• Define engineering best practices (CI/CD, unit testing for AI, code reviews) and cascade design patterns to data engineers.
• Develop and optimise full‑stack interfaces (front‑end and API layers) for high availability and low latency.
• Conduct deep‑dive research into emerging Agentic technologies and prototype their application within legacy banking infrastructure.

Required profile

• Degree in Mathematics, Statistics, Computer Science, Management Information Systems or a related field.
• 4‑5 years of total software engineering experience, including at least 2 years developing, implementing, and deploying LLM‑based applications.
• Hands‑on experience building production‑grade LLM‑powered applications or strong proof‑of‑concepts.
• Strong programming skills in Python and proficiency in SQL for data transformation and analytics.
• Deep understanding of vector‑database architectures (e.g., Milvus, Pinecone) and advanced Retrieval‑Augmented Generation (RAG) strategies.
• Experience setting up LLM Ops / MLOps pipelines covering CI/CD, evaluation, and monitoring.
• Relevant certifications or training (e.g., Google AI, Kaggle, OpenAI) are a plus.

Required skills

• Python
• SQL
• Milvus
• Pinecone
• CI/CD
• ML Ops
• Prompt Engineering
• Agentic Orchestration
• Multi‑Agent Systems
• Retrieval Augmented Generation (RAG)