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# AI Engineer

- **Company:** RISE INC
- **Location:** Boston, MA, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Python (Programming Language), Language Modeling, Software Architecture, Software Deployment, Software Engineering, Systems Integration, Scripting, AI Platforms, Information Technology
- **Published:** November 11, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-engineer-boston-ma--4bcf5634-70f2-41eb-9f34-725d65025224

## About the Role

Artificial Intelligence (AI), Startup, Artificial Intelligence (AI), Resolve Customer Issues, Research Laboratory, Sales Closing Skills, Modeling Languages, Application Programming Interface (API), Python Programming/Scripting Language, Customer Relations, * 6 to 12 years in back end or AI engineering, building and deploying large language model systems in production.

 * Your last 2 to 3 years as an engineer at a high growth, venture backed Series A through Series D AI startup shipping product to enterprise customers.
 * Large language model or agentic workflows you built and shipped that run in production for external customers. Internal tools and prototypes do not count.
 * Strong software architecture and system design, and the ability to own technical delivery end to end.
 * Back end or full stack software engineering in Python.
 * A degree in computer science or a related field.
 * Experience working directly with enterprise customers or their technical teams, ideally in banking or another regulated industry.
 * You live on the US East Coast and work Eastern time hours.

## Description

This role is remote, and you must work Eastern time hours. New York is preferred. Candidates on West Coast or Central time are not a fit.

We are helping a venture backed Series A AI startup hire AI engineers. The company builds custom AI systems that carry approved, high stakes work across the systems a large regulated enterprise already uses, including older private systems.

Each deployment is a tailored version of the core platform, run end to end inside the customer's own environment, because data in these industries cannot leave the customer's infrastructure. The customer's policies decide what the system can do. When a judgment call is needed, the work goes back to a person with the evidence already assembled. Every run leaves an audit trail. Operating data stays with that customer and is not shared. The company can run on the customer's chosen foundation model, and it keeps control of its own model stack, including its own compute.

The company works like an applied research lab that cares most about getting models into production and solving customer problems. The team has strong research backgrounds. Many of the research and engineering people have worked together before, including at a previous company the founders built. It has closed large enterprise deals with major financial institutions and is growing quickly. The core engineering team is overseas, and the US team overlaps with it on Eastern time. The structure is flat, and engineers own their work end to end. A New York office is being set up.

What you will do

 * Own the technical build of a customized version of the company's AI platform for a major enterprise customer, from architecture to deployment.
 * Adapt and extend the core platform for the customer's environment, and merge customer specific work back into the main product.
 * Work every day with the core engineering team abroad, overlapping on Eastern time.
 * Own production deployments, integrations and the reliability of large language model systems in a regulated enterprise environment.
 * Build back end and full stack features in Python: APIs, integrations and deployments for AI powered products.
 * Serve as a go to technical contact for the customer's engineering stakeholders. Expect about 20 percent of your time to be customer facing.
 * Troubleshoot complex production issues and drive fixes end to end with a high degree of independence.
 * Help shape how the US engineering team works as it grows.