Artificial Intelligence Engineer

About the job

We are seeking a highly skilled and motivated AI Engineer to join our team in developing reusable AI-powered tools and components that drive automation, scalability, and efficiency across our technical delivery ecosystem. This role will focus on leveraging large language models (LLMs) to develop intelligent, context-aware automation tools, starting with a flagship tool that automates SQL script generation for data migrations and transformations.

Youll work closely with solution architects and data engineers to build generative AI assets that can be integrated into repeatable client delivery work-streams especially for non-profit and education clients using platforms like Salesforce Non-profit Cloud, Education Cloud, Salesforce NPSP, Raisers Edge, and Ellucian Banner.

Key Responsibilities :

- Design and Develop AI-Powered Tools Build generative AI tools and services, such as automated SQL generation engines, that reduce manual coding effort and increase accuracy.

- Prompt Engineering and Tuning Craft and optimize prompts to drive high-quality outputs from foundation models. Fine-tune LLMs or use APIs to adapt model behaviour to specific use cases.

- Integrate LLMs into Business Workflows Embed LLM-powered components into scalable, reusable applications that can be integrated into delivery processes or client-facing solutions.

- Data Contextualization and Reasoning Develop solutions that use structured or semi-structured data inputs to generate context-aware outputs, applying reasoning over business logic, schemas, or documentation.

- Leverage LLMs for Contextual Understanding Develop tooling that uses large language models to interpret source data structures, target schemas, and mapping documents to generate tailored data migration scripts.

- Collaborate with Cross-Functional Teams Work closely with data engineers, product managers, and solution architects to identify use cases and deliver effective AI-enhanced capabilities.

- Ensure Model Safety and Performance Monitor and evaluate LLM-generated outputs for accuracy, safety, and consistency. Implement validation, fallback logic, and usage controls as needed.

- Drive Reusability and Knowledge Capture Develop modular, reusable components that can be easily adapted for new use cases and contribute to a growing library of internal IP.

- Perpetually contribute to the betterment of Cloud for Good

- Be prepared to work in shifts to accommodate our global customer base across different time zones, including the AMER, APAC, and EMEA.

Qualifications :

- Proven experience building with LLMs or other generative AI models (e.g., OpenAI, Claude, or open-source frameworks like LLaMA).

- Strong background in Python, with hands-on experience using AI/ML libraries (e.g., LangChain, Hugging Face, transformers).

- Solid understanding of SQL and data engineering workflows, particularly related to data migration and transformation.

- Experience working with or integrating structured data systems like SQL, Salesforce, Raisers Edge, and Banner.

- Ability to build context-aware, prompt-engineered solutions that integrate with APIs or internal systems.

- Familiarity with MLOps or DevOps practices for deploying and monitoring AI applications is a plus.

- Excellent communication skills and ability to translate complex AI functionality into real-world business value.

Preferred Skills :

- Exposure to Salesforce ecosystem tools and data models.

- Experience contributing to internal toolsets or reusable IP in a professional services or consulting environment.

- Prior experience working with data migration frameworks or ETL pipelines.