Senior Data and AI Engineer

Position Summary

Panacea Financial Holdings is seeking a Senior Data and AI Engineer to design, develop, and maintain scalable AI solutions and the data infrastructure supporting our financial technology platform.

This role will play a key part in advancing Empower, our conversational AI platform, and developing internal AI applications that support business operations and decision making. The ideal candidate brings strong experience in AI engineering, data engineering, and cloud infrastructure, with the ability to build reliable, secure, and production-ready solutions.

Working within a collaborative technical team, this individual will help establish engineering standards, improve AI performance, and ensure solutions meet the security and compliance requirements of a regulated financial environment.

Key Responsibilities

AI Engineering & Development

• 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.

Data Engineering & Governance

• 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.

Cloud Infrastructure & AI Operations

• 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.

Testing, Evaluation & Continuous Improvement

• 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.

Collaboration & Technical Leadership

• 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.

Qualifications & Experience

• 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 large language model (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, retrieval-augmented generation (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.

Preferred Qualifications

• 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.

Skills & Competencies

• 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.