AI Engineer

Duties and Responsibilities

• Help develop and refine PTMA's enterprise Claude deployment, including prompt design, custom skills, and configuration, under the direction of senior team members.
• Build and maintain AI-powered automations across business units such as Finance, Compliance, Sales, and Operations.
• Work with team leads to map manual processes and deliver measurable time savings.
• Partner with internal departments to develop and refine AI skills, plugins, and integrations that connect to internal systems, including Salesforce and our data pipelines.
• This cross-functional partnership is a core part of the role.
• Build and maintain integrations and custom tooling, such as MCP integrations and API connections, that let AI work with PTMA's systems and data.
• Contribute to data and analytics engineering work as needed, including dbt models, Microsoft Fabric and Azure Data Factory pipelines, SQL Server and Azure SQL, and Power BI reporting, to support AI, forecasting, and public finance use cases.
• Support responsible AI practices in line with SEC, FINRA, and NIST CSF requirements, including data handling, output review, and audit-ready documentation.
• Work with InfoSec and Compliance to help keep AI usage safe and governed.
• Help drive adoption by writing clear user guides, running training sessions, and explaining what AI can and cannot do to non-technical colleagues.

Required Skills And Abilities

• Hands-on experience building with large language models, including prompt engineering and putting AI-assisted workflows or automations into real use.
• Working knowledge of data engineering concepts, including APIs, data pipelines, and structured and unstructured data.
• Proficiency in Python, or a comparable language, for AI integration and scripting.
• Strong analytical skills and the ability to translate a business need into a practical AI or data solution.
• Ability to explain AI capabilities and limitations clearly to non-technical colleagues.
• Comfort working in or supporting a regulated environment, with attention to data privacy and responsible AI practices.

Education and Experience

• 2 to 5 years of professional experience in software, data, or analytics engineering, including hands-on experience building with large language models.
• LLM experience can be demonstrated through shipped work, a portfolio, production deployments, or internal tools.
• We are not looking for years in a titled AI role.

Preferred Qualifications

• Direct Anthropic Claude experience, including API usage, custom skill creation, and MCP server integration.
• Claude Certified Associate - Foundations (CCAO-F) or Claude Certified Architect - Foundations (CCAR-F) certification through the Anthropic Claude Certification Program.
• Experience with Microsoft Fabric, Azure, SQL Server or Azure SQL, and Power BI.
• Experience with Salesforce and AI use cases in CRM ecosystems.
• Experience in or supporting U.S.-regulated financial services, treasury management, or public-sector technology.
• Familiarity with Azure cloud services in data and AI-adjacent workloads.
• Exposure to SOC 2, NIST CSF, or FINRA and SEC regulatory technology requirements.
• Interest in contributing to internal AI governance practices and centers of excellence.