Lead AI Engineer

Eastern Bank

About The Position

Eastern Bank is seeking an AI Engineer to build and scale enterprise AI capabilities across the bank. This hands-on role involves developing AI agents and automated workflows, building retrieval and prompt systems, and supporting the integration of AI tools within business divisions. The position combines technical development with business enablement, translating non-technical use cases into working technical solutions.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
  • 1–4 years of experience in software engineering, data/ML engineering, or a related technical role.
  • Experience working with LLM-based tools and enterprise cloud and collaboration platforms.
  • Hands-on experience with LLM-based tools such as Claude, OpenAI, Gemini, or similar, including prompt engineering and/or agent frameworks.
  • Familiarity with the Microsoft ecosystem, such as Azure, Copilot, Power Platform, or M365 administration and development tools.
  • Comfort working with APIs, MCPs, basic data pipelines, and integration patterns.
  • Knowledge of AI governance, tool administration, and responsible AI considerations.
  • Strong communication skills, including the ability to translate a non-technical stakeholder’s workflow into a technical plan.

Nice To Haves

  • Experience in a regulated industry, such as financial services.

Responsibilities

  • Design, build, and maintain AI agents and automated workflows using Claude tools and Microsoft-based tooling, including Copilot, SharePoint, Power Platform, and Azure AI services.
  • Develop reliable, maintainable retrieval-augmented generation (RAG) pipelines and prompt systems.
  • Partner with business units across divisions to understand workflows and pain points and translate use cases into clear technical specifications.
  • Serve as a technical resource and enablement partner for embedded AI roles within business divisions.
  • Build and refine retrieval systems and prompt architectures to improve agent accuracy and reliability.
  • Prototype solutions and move them from proof of concept to embedded, day-to-day use across the bank.
  • Help develop and document workflows to govern and administer enterprise AI tools, including access provisioning and usage policies.
  • Support responsible AI practices, including appropriate data handling and permissions in a regulated banking environment.

Benefits

  • Robust benefits and retirement package.
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