AI Integration Engineer

We offer a flexible working policy that supports a healthy balance between personal and professional well-being. This role requires in-office presence on Tuesdays & Thursdays to collaborate, connect, and learn from peers - while also maintaining the flexibility for meaningful work-life balance.

You will own agentic and AI-driven integration development, along with the development and operations practices needed to run what you build. You will develop autonomous agents that respond to data, events, or AI models, including both large language models and internally developed machine learning models, to independently carry out tasks. You will approach this work with a Databricks-first mindset, using Claude where it is the best fit for the outcome.

You will build applications that extend enterprise data to the organization using tools such as Databricks Apps, and you will contribute to the ongoing development of the Ask iMData MCP connector — our MCP server that interfaces with Databricks and our enterprise data sources — including its continued support of go-to-market data and AI use cases.

• Development of autonomous agents based on data, events, or AI models (both large language models and internally developed machine learning models) that respond to triggers and signals to autonomously perform a given task.
• Developing agentic AI with a Databricks-first mindset, utilizing Claude where best suited to meet the desired outcomes.
• Developing applications for extending enterprise data to the organization using the tools appropriate to complete the task, such as Databricks Apps.
• Contributing to ongoing development and management of our MCP server that interfaces with enterprise data and Databricks.
• Working collaboratively with business analysts and business stakeholders to understand the desired outcomes, the underlying processes that support the desired business outcomes, and evaluating where an autonomous agent is an appropriate solution, with initial emphasis on go-to-market systems and workflows.
• Working collaboratively with the iManage Process Center of Excellence to ensure processes executed by autonomous agents and the processes for monitoring those agents are thoroughly captured and maintained.
• Defining and developing methods for monitoring agent operations (e.g., completion, data flow, and timing; alerting on failures/quality/API errors; tracking SLAs; documenting dependencies).
• Iterating on agents to make performance improvements measured by metrics, such as safety, accuracy of tool selection, task completion rate, etc.
• Designing and maintaining event architecture triggers that launch and orchestrate agents.
• Working collaboratively with Data Governance to define and apply standards for naming conventions.
• Working collaboratively with Data Governance to define and apply standards for logging and auditing agent operations.
• Applying change management standards for agents and integrations as defined by the Data Governance team.
• Preparing and maintaining technical documentation of agents and integration operations to record, at a minimum, model dependencies, activation triggers, workflows, and data sources.
• Managing incidents for its integrations: triage, escalation, severity, runbooks, on-call, and vendor escalation.

• A master’s degree or higher in computer science, engineering, or an equivalent field.
• 1-2 years of experience developing autonomous agents or agentic AI solutions, including working with large language models (e.g., Claude) and/or internally developed machine learning models.
• Proficiency in programming languages such as Python (preferred), Java, or C#.
• Experience using SQL to query and manipulate…