AI Engineer

Responsibilities

• 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, One Reach.ai, Lang Chain 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 Dev Ops 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.

• Experience operating within a senior or lead software engineering position with a full stack developer background
• Experience using React.
  
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• Azure Cloud experience of at least 5+ years
• Exposure to building AI solutions, with experience shipping production solutions.
• Ability to write clean, testable, and scalable code with Python, C# or JS.
• Demonstrable production experience with AI Foundry Orchestration, Lang Chain, One Reach.ai or similar AI orchestration frameworks.
• Proven experience developing AI agents and agentic workflows for commercial applications.
• Experience leading technical projects from design through to production deployment.
• Strong communication and stakeholder management skills, with the ability to confidently present technical solutions and architectures to clients and senior stakeholders.