Principal AI Engineer - Servicing Solutions

Key Responsibilities

• Architect and develop scalable AI-driven tools integrated with Large Language Models (LLMs) and multi-agent systems to drive automation and enhance decision-making.
• Build and implement retrieval-augmented generation (RAG) and knowledge management systems to enhance AI-powered insights and recommendations.
• Lead AI strategy, collaborating closely with engineering, data, and product teams to align AI initiatives with strategic business objectives.
• Evaluate and integrate third-party LLMs, AI models, APIs, and agentic frameworks.
• Mentor engineers on best practices in AI/ML, fostering a culture of continuous learning and technical excellence.
• Ensure AI solutions meet regulatory standards, including SOC 2, PCI-DSS, and ethical guidelines.
• Collaborate on model fine-tuning, deployment, and MLOps practices with assistance from other team members.

Qualifications

• 10+ years of experience in software engineering, with at least 2+ years working with AI/ML solutions or LLMs.
• Excellent leadership and problem-solving skills, with the ability to drive AI strategy at scale.
• Strong software architecture and design skills, with experience building and improving distributed systems and full-stack applications and web products
• Some hands-on experience with AI model development, fine-tuning, and deployment using frameworks like PyTorch, TensorFlow, Hugging Face.
• Significant hands-on experience with LLM APIs, agent frameworks, platforms, and protocols such as OpenAI API, AWS Bedrock, LangChain, Semantic Kernel, Model Context Protocol.
• Expertise in Python and TypeScript, with experience in building AI-driven backend systems.
• Experience in .NET (C#) preferred but not required.
• Experience working with vector databases, embeddings, and semantic search.
• Strong understanding of machine learning principles, prompt engineering, and AI inference optimization.
• Familiarity with MLOps, CI/CD for AI pipelines, and AI observability tools.
• Knowledge of financial services applications, including risk assessment, fraud detection, and AI-driven process automation.