Senior Data and AI Engineer

Panacea Financial Holdings is seeking a Senior Data and AI Engineer to build and maintain scalable AI solutions and the data infrastructure supporting its financial technology platform. The role advances its conversational AI platform and internal AI applications while establishing engineering standards and meeting security and compliance requirements.

Responsibilities:

• Design, build, and maintain AI applications, including conversational AI, AI agents and agentic workflows, model integrations, and governed tools using Model Context Protocol (MCP) or similar frameworks
• Develop and optimize prompts, AI workflows, and evaluation processes to ensure accurate, reliable, and efficient outputs
• Leverage agentic coding tools to accelerate development while maintaining strong code quality, testing, and human review standards
• Partner with Product and business stakeholders to translate requirements into practical AI solutions
• Develop and maintain data pipelines, integrations, and governed data models using Snowflake, SQL, dbt, and related technologies
• Support data quality, consistency, and customer data integration across systems
• Implement appropriate data access controls, security measures, and governance practices to protect sensitive information
• Deploy, monitor, and maintain AI and data services in cloud environments, primarily Azure and Snowflake
• Develop and maintain CI/CD pipelines, infrastructure automation, and reliable release processes
• Monitor system performance, reliability, latency, and token and compute costs using LLM observability tools, identifying opportunities for improvement
• Collaborate with IT and engineering teams to maintain secure infrastructure and operational standards
• Develop testing and evaluation frameworks to assess AI accuracy, performance, and reliability
• Identify and resolve technical issues through testing, monitoring, and user feedback
• Maintain documentation, technical standards, and processes that support responsible AI development and deployment
• Serve as a technical resource for AI engineering and related development initiatives
• Collaborate with engineering, analytics, IT, Product, and business teams on cross-functional projects
• Mentor colleagues, share best practices, and contribute to continuous improvement of engineering standards
• Communicate technical concepts and recommendations clearly to technical and nontechnical stakeholders