AI Enablement Engineer

InterSystems•Boston, MA

10h

About The Position

The AI Enablement team serves as a central hub for accelerating AI adoption across InterSystems while maintaining trust, consistency, and governance. We operate with a portfolio mindset, balancing innovation with risk, with the goal of increasing AI adoption and ROI across the business. Team members work directly with individuals across the globe including product engineering teams, implementation teams, and customer-facing groups, and are expected to communicate clearly, make sound trade-offs, and drive alignment in complex, fast-moving environments. The AI Enablement Engineer is a senior technical leader responsible for accelerating the quality, speed, and consistency of AI delivery across InterSystems products, services, and internal teams. This role does not focus on building one-off models; instead, it establishes the technical “paved roads, reusable architectures, components, evaluation frameworks, and best practice, that enable teams and customers to deliver trusted AI at scale. The role offers a fantastic opportunity to gain experience across a range of technologies, to solve interesting problems, to be allowed to make improvements, and to be recognized for making a difference.

Requirements

4+ years in software engineering, data engineering, or ML/AI – Essential
Hands on experience with GenAI Systems (LLMs, Coding assistants, RAG tools, vector databases, orchestration, embedding models, client libraries) – Essential
Experience with 2-3 common programming languages (python, java, .NET, C/C++/ etc.) – Essential
Understanding of LLM flows: Prompting, Guardrails, AI Security, Agentic Flows– Essential

Nice To Haves

Experience with AI Engineering, Finetuning, GPU optimization, Hosting, VLLM– Pref
Experience and knowledge of Containerization, Databases, SQL– Pref
Experience with bleeding edge AI tooling, such as Claude Code, and newer agentic frameworks. – Perf

Responsibilities

Define and Implement reference architectures for AI use within InterSystems Processes.
Build reusable components and libraries for AI Coding Assistants (Claude Code, Codex, Copilot, etc).
Manage and maintain repositories of AI internal helpers.
Establish technical best practices for AI lifecycle stages: build, validate, deploy, monitor.
Partner with compliance groups to embed safe-by-design practices: security, legal, governance.
Contribute to GenAI workbooks, training context, and enablement materials.
Evaluate AI tools and platforms as they are requested, including new SOTA and OSS model releases, tooling, and common patterns seen in the marketplace.
Act as a technical leader and multiplier, mentoring engineers and influencing architecture decisions across the company.