Senior AI Engineer

• Owns end-to-end development and delivery of AI, ML, and LLM-powered solutions from design through production. 

• Acts as a technical authority for AI architecture, frameworks, and model lifecycle management. 

• Ensures data governance, security, compliance, and operational stability across AI deployments. 

• Proactively identifies blockers, defines mitigation approaches, and drives disciplined execution. 

• Maintains accountability for reliability, scalability, and long-term maintainability of AI systems. 

Drives Efficiency 

• Improves platform intelligence, latency, scalability, and operational performance through optimization and observability. 

• Defines and applies technical KPIs for accuracy, inference performance, and system health. 

• Builds reusable components, services, and standards that accelerate AI development and reduce duplication. 

• Implements automation through MLOps pipelines, monitoring, and evaluation workflows. 

• Uses data-driven feedback loops to continuously improve model behavior and system efficiency. 

Innovative 

• Evaluates and prototypes emerging AI technologies including LLMs, agentic frameworks, and multimodal systems. 

• Uses GenAI tools such as Azure OpenAI, LangChain, and Semantic Kernel to accelerate experimentation and delivery. 

• Leads applied experimentation to validate new approaches and evolve AI architecture patterns. 

• Advances self-learning, monitoring, and automation strategies that strengthen AI delivery at scale. 

• Applies creative problem-solving to complex AI challenges across the platform. 

Customer Centric 

• Designs AI-powered capabilities that enhance payer engagement, personalization, and operational outcomes. 

• Collaborates with Product and Client-facing teams to ensure AI solutions align with real customer needs. 

• Incorporates feedback loops to measure business impact and refine AI behavior over time. 

• Advocates for responsible AI practices that emphasize fairness, transparency, and trust. 

• Ensures AI systems deliver predictable, high-quality experiences in customer-facing workflows. 

Requirements 

• 9+ years of software engineering experience, including 3+ years building AI, ML, or LLM-powered applications 

• Proven success delivering scalable, production-grade AI systems in a SaaS environment 

• Strong proficiency in Python and C#, with experience using Azure OpenAI, LangChain, Semantic Kernel, FastAPI, and vector databases 

• Deep understanding of model evaluation, prompt tuning, inference optimization, and observability 

• Experience designing, deploying, and operating AI pipelines and services 

• Strong analytical, communication, and collaboration skills 

• Experience mentoring engineers or influencing technical design and standards