Systems Operations Engineer, NLP, LLM

About the Role

As a senior technical leader and hands-on developer, you will be responsible for creating advanced voice-driven AI agent solutions tailored to the needs of banking and financial services. This position places a strong emphasis on innovation in Agentic AI, conversational AI, and voice interfaces, along with the development of autonomous decision-making agents that leverage Microsoft’s latest AI and cloud technologies.

In this role, you will design and launch AI systems within regulated enterprise environments, ensuring that these systems are scalable, secure, and reliable. Your success will be measured by the robust, transformative AI capabilities you deliver, which enhance customer experiences and improve operational efficiency. Throughout your work, you will maintain the highest standards of quality, compliance, and performance.

What You Will Be Doing

• 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.

• Agentic Workflows & Orchestration: 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.

• Quality, Observability & Optimization: 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.

• Security & Responsible AI: 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.

• Collaboration & Leadership: 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.

What you bring

• Extensive Industry Experience: Proven experience (e.g. 5+ years) in software development and architecture, building large-scale AI or cloud-based solutions in production environments.

• AI & Voice Expertise: 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.

• Microsoft Azure and AWS Proficiency: Strong experience developing with Microsoft Azure and AWS cloud services. Knowledge of CI/CD, Azure and AWS container services for deploying AI workloads.

• Programming & DevOps Skills: 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.

• System Design & Architecture: Deep knowledge of scalable, distributed systems designs and cloud-native architecture. Experience implementing microservices, containerization, and API integration.

• Problem Solving & Innovation: 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.

• Communication: Excellent communication skills, with ability to explain complex AI solutions and technical strategies to diverse stakeholders.

Bonus if you have

• Financial Services Familiarity: Experience working in banking, fintech, or other heavily regulated industries and understanding of compliance, security, and data privacy considerations for AI solutions in these environments.

• AI Research & Innovation: Demonstrated interest in emerging AI trends (such as agentic AI, multi-modal models, reinforcement learning, etc.) and experience bringing new AI concepts from prototype to production.

• Advanced Degree: Master’s or higher degree in Computer Science, Engineering, AI, or related field (or equivalent practical experience) is a plus.