Applied AI ML Lead Software Engineer – LLM Suite Engineering

Overview

In this role you will drive hands-on engineering for agentic AI and GenAI capabilities within the LLM Suite platform, shaping scalable, production-grade AI solutions. You will own architectural direction, collaborate across engineering teams, and advance secure software delivery in a cloud-centric environment. You’ll transform early-stage AI concepts into reliable, operational capabilities while contributing to a culture of learning and security. This is a high-impact opportunity to influence how AI-powered systems scale in a global financial services context.

Responsibilities

• Design, develop, and troubleshoot software solutions to solve complex challenges
• Write secure, production-ready code and maintain algorithms that integrate with existing systems
• Create architecture and design artifacts ensuring constraints are met
• Build AI/ML solutions and agentic systems for the LLM Suite on Azure, AWS, and modern agentic frameworks
• Implement GenAI services using Azure OpenAI models and AWS Bedrock
• Identify hidden data problems to improve coding standards and system architecture
• Participate in communities of practice and events focused on emerging technologies

Key requirements

• Computer science degree or equivalent practical experience
• Hands-on experience with system design, application development, testing, and operational stability
• Proficiency in Python (FastAPI)
• Experience building microservices and APIs
• Experience with elastic compute, NoSQL databases, and messaging queues
• Strong understanding of the Software Development Life Cycle
• Solid grasp of CI/CD, application resiliency, and security

• collaboration across teams
• problem-solving mindset
• continuous learning
• GenAI services leveraging Azure OpenAI models and AWS Bedrock
• LangGraph for building agents
• large language models experience

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