Systems Operations Engineer, NLP, LLM

About the role

This position involves designing and launching AI systems within regulated enterprise environments, focusing on innovation in Agentic AI, conversational AI, and voice interfaces. Key responsibilities include building voice-based autonomous agents and conversational AI for banking platforms, integrating LLM models and cognitive services, and ensuring high standards of quality, compliance, and performance.

Responsibilities

• Build voice-based autonomous agents and conversational AI for banking platforms using Microsoft Dynamics 365 Contact Center, Agent SDK, Microsoft Power Platform (Copilot studio, Dataverse, Power Apps, Power Automate, Power Pages), and Azure AI services (Azure OpenAI, Azure AI Speech, Bot Framework, etc.).
• Integrate LLM models and cognitive services (e.g. OpenAI models, Azure AI Speech (STT/TTS), Azure AI Foundry, AWS Sagemaker/bedrock) into enterprise applications to deliver natural language and voice interactions.
• Build agentic workflows that allow AI to perform complex, multi-step tasks autonomously. Develop orchestration logic and use container services in AWS and Azure (AKS, EKS, ECS etc.) and microservices architectures to ensure these AI agents run efficiently in production.
• Implement robust monitoring, logging, and observability for AI services. Continuously optimize performance (latency, accuracy) of voice and AI systems using Azure and AWS monitoring tools to ensure high availability, reliability, and compliance.
• Embed security, privacy, and Responsible AI best practices into all solutions. Ensure data protection and regulatory compliance (relevant to banking/financial industry) while enabling advanced AI capabilities.
• Collaborate with cross-functional teams (business analyst, data scientists, designers, cloud engineers, and architects) to deliver cohesive AI-powered features. Mentor and guide fellow engineers in modern AI-first development practices, setting high standards in coding, testing, and deployment.

Requirements

Extensive industry experience (e.g. 5+ years) in software development and architecture, building large-scale AI or cloud-based solutions in production environments. Hands-on expertise with AI/ML technologies, including natural language processing (NLP) or speech recognition. Familiarity with large language models (e.g., GPT, Claude or similar) and conversational AI/voice assistant development. Strong experience developing with Microsoft Azure and AWS cloud services. Knowledge of CI/CD, Azure and AWS container services for deploying AI workloads. Proficient in modern programming languages (such as Python, Java, C#, or similar) and building APIs or microservices. Solid understanding of DevOps and CI/CD practices (e.g., Azure DevOps pipelines) to ensure frequent, reliable delivery of AI software. Deep knowledge of scalable, distributed systems designs and cloud-native architecture. Experience implementing microservices, containerization, and API integration. Strong analytical and problem-solving skills with the ability to navigate complex technical challenges. Innovative mindset to drive continuous improvement and to evaluate emerging technologies for potential adoption. Excellent communication skills, with ability to explain complex AI solutions and technical strategies to diverse stakeholders. Master’s or higher degree in Computer Science, Engineering, AI, or related field (or equivalent practical experience) is a plus.

Qualifications

Desired Bachelor of Computer Science.

Skills

Extensive industry experience (e.g. 5+ years) in software development and architecture, building large-scale AI or cloud-based solutions in production environments. Hands-on expertise with AI/ML technologies, including natural language processing (NLP) or speech recognition. Familiarity with large language models (e.g., GPT, Claude or similar) and conversational AI/voice assistant development. Strong experience developing with Microsoft Azure and AWS cloud services. Knowledge of CI/CD, Azure and AWS container services for deploying AI workloads. Proficient in modern programming languages (such as Python, Java, C#, or similar) and building APIs or microservices. Solid understanding of DevOps and CI/CD practices (e.g., Azure DevOps pipelines) to ensure frequent, reliable delivery of AI software. Deep knowledge of scalable, distributed systems designs and cloud-native architecture. Experience implementing microservices, containerization, and API integration. Strong analytical and problem-solving skills with the ability to navigate complex technical challenges. Innovative mindset to drive continuous improvement and to evaluate emerging technologies for potential adoption. Excellent communication skills, with ability to explain complex AI solutions and technical strategies to diverse stakeholders. Master’s or higher degree in Computer Science, Engineering, AI, or related field (or equivalent practical experience) is a plus.

Benefits

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EEOC Statement
FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here
For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test.

Pay

TBD

Schedule

TBD