Senior Software Engineer - AI/ML

Job Overview

We are seeking a highly skilled Senior Software Engineer specialising in Generative AI and Large Language Models, with a strong focus on agentic systems, Retrieval-Augmented Generation, and AI evaluations, to join our dynamic team. The ideal candidate will play a pivotal role in architecting and delivering production-grade AI solutions that meet complex business objectives effectively. This position requires a blend of expertise in modern AI technologies and software engineering, along with a passion for staying at the forefront of advancements.

Essential Duties & Responsibilities

• Design, build, and operate multi-agent workflows and tool-enabled agents, implementing orchestration logic, state management, safety guardrails, and fallback strategies for resilient production pipelines.
• Architect and maintain end-to-end RAG systems, covering document ingestion, chunking, embedding, vector retrieval, reranking, and answer synthesis with a focus on quality, attribution, and latency.
• Evaluate and integrate LLMs and GenAI services across cost, performance, and privacy dimensions, selecting the right mix of managed and in-house models.
• Develop, version, and optimise prompting strategies; implement automated prompt testing and regression tracking to maintain output quality and reliability.
• Define and own evaluation frameworks for generative outputs, including automated metrics, LLM-as-judge approaches, human evaluation protocols, hallucination detection, and drift monitoring.
• Apply classical NLP techniques where appropriate and maintain awareness of data distribution shifts that could impact model behaviour in production.
• Build and operate scalable, secure AI infrastructure on AWS (Bedrock, SageMaker, Lambda, OpenSearch), following well architected principles and infrastructure-as-code practices.
• Own the full deployment lifecycle: CI/CD for models and agents, testing strategies, observability, and rollback procedures.
• Ensure data quality through rigorous validation and augmentation, and proactively source datasets for training, fine-tuning, and evaluation.

Requirements & Skills

• Agent Orchestration: Production experience designing multi-agent systems with tool use, memory/state management, and fault-tolerant routing. Familiarity with LangChain, LangGraph, AutoGen, or custom orchestrators.
• RAG & Retrieval: Hands-on experience building RAG pipelines end-to-end: chunking, embedding models, vector databases, retrieval tun