Senior Data and AI Engineer

Panacea Financial•Westlake, OH

About The Position

Panacea Financial Holdings is seeking a Senior Data and AI Engineer to design, develop, and maintain scalable AI solutions and the data infrastructure supporting its financial technology platform. The role will advance Empower, the company’s conversational AI platform, and develop internal AI applications that support business operations and decision-making. The engineer will build reliable, secure, production-ready solutions and help establish engineering standards, improve AI performance, and meet the security and compliance requirements of a regulated financial environment. The role combines AI engineering, data engineering, cloud infrastructure, AI operations, testing, and technical leadership. It includes developing AI applications and governed data systems, operating services primarily in Azure and Snowflake, and collaborating with technical and business teams to deliver responsible, secure solutions.

Requirements

At least 6 years of relevant experience in AI engineering, software engineering, data engineering, cloud infrastructure, or related fields.
Hands-on experience developing, deploying, and maintaining AI or LLM applications in production environments.
Strong proficiency in Python and SQL, with experience in TypeScript/React or comparable frameworks.
Experience with cloud data platforms such as Snowflake and data transformation tools such as dbt.
Experience with AI and agent frameworks, RAG, tool integrations, prompt engineering, and evaluation methodologies.
Hands-on experience with agentic development tools such as Claude Code, OpenAI Codex, Cursor, Devin, or Pi, including reviewing, testing, and validating AI-generated code.
Experience with cloud infrastructure, preferably Azure, including CI/CD pipelines, agent harnesses and orchestration, infrastructure as code, and containerized applications.
Understanding of data governance, security, access controls, and responsible AI practices.
Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience.
Strong technical judgment and commitment to accuracy, reliability, and security.
Ability to work independently, prioritize competing needs, and solve complex technical challenges.
Adaptability and willingness to learn and implement emerging AI technologies.
High level of accountability and ownership of technical solutions.

Nice To Haves

Experience with MCP, Azure AI Foundry, Snowflake Cortex, or similar AI platforms.
Experience with data ingestion, change data capture, entity resolution, or semantic data modeling.
Familiarity with identity management, secrets management, and cloud network security.
Experience in financial services, banking, healthcare, or other regulated industries.
Experience mentoring engineers or leading technical initiatives.

Responsibilities

Design, build, and maintain AI applications, including conversational AI, AI agents and agentic workflows, model integrations, and governed tools using MCP or similar frameworks.
Develop and optimize prompts, AI workflows, and evaluation processes for accurate, reliable, and efficient outputs.
Use agentic coding tools to accelerate development while maintaining 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 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, and identify 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 supporting 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.