Abstract Group

AI Engineer

• Lead the development of AI solutions across multiple client engagements.
• Collaborate with Abstract Customer Engagement and clients to understand business challenges and translate them into AI-driven solutions.
• Work with client data teams to ingest, clean, and prepare data for modeling.
• Build and integrate AI solutions using Azure AI Foundry, OneReach.ai, LangChain or similar orchestration frameworks for conversational AI.
• Design and optimise Retrieval-Augmented Generation (RAG) pipelines, including embedding generation, vector database configuration, API, MCP and retrieval tuning to improve accuracy, latency, and relevance in conversational AI.
• Prompt optimisation of closed source LLMs, or post-training of open-source LLMs to build new or improve existing agentic workflows.
• Understand and guide on evaluation frameworks to measure model safety, accuracy, and performance, including recall, precision, F1-score, and other relevant metrics for both conversational AI and classification models.
• Collaborate with our DevOps team to produce MLOps pipelines to speed up experimentation, deployment, and monitoring.
• Ship AI models into live production environments and iterate rapidly based on usage, feedback, and metric-driven insights.
• Write clean, testable, and scalable code in .NET or Python and integrate with backend services.
• Stay up-to-date with the latest AI research and tools, applying them pragmatically to solve real problems.
• Design and refine prompts, workflows, and evaluation frameworks for autonomous AI financial analysts.

Consultant

• Act as a trusted advisor to clients and stakeholders, providing guidance on delivery approaches, technical considerations and best practice.
• Lead discovery workshops and requirements gathering activities, translating business needs into technology solutions and delivery roadmaps.
• Produce and oversee high-quality delivery artefacts, including SOWs, technical specifications and project documentation.
• Define solution scope and collaborate with engineering and architecture teams to ensure solutions are technically feasible, scalable and aligned to client requirements.
• Define, refine and prioritise requirements, ensuring clear backlogs, acceptance criteria and delivery priorities.
• Own the successful delivery of large, complex, or high-risk client engagements.
• Establish effective delivery governance, reporting structures and ways of working across projects and workstreams.
• Lead cross-functional teams across engineering, QA, design, and third-party vendors.
• Monitor delivery performance and drive continuous improvement across teams, processes and tooling.
• Contribute to pre-sales and bid processes, shaping proposals and estimating delivery effort.
• Manage project financials, change control and commercial performance while identifying opportunities for account growth and maintaining high levels of client satisfaction.
• Manage delivery risks and ensure appropriate quality, testing and release management practices are followed.
• Provide clear, data-driven reporting to stakeholders, including senior leadership.

AI Engineer

Senior Client Delivery Consultant