AI Engineer

Lucentive; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Remote work with CET overlap

Occasional travel

Job summary

Lucentive seeks an engineer to build and maintain the runtime that makes AI agent outputs traceable and reviewable across engagements. The role integrates tools, memory, and retrieval to support diverse validation needs and provides observability into how outputs are produced.

You will implement extraction pipelines with confidence scores and source references, handle imperfect inputs, and ship validators and audit trails.

Qualifications

• Experience shipping AI or agent systems into production with strong typed software engineering practices.
• Experience building evaluation or monitoring systems that detect meaningful regressions.
• Ability to handle imperfect real-world inputs such as scans, inconsistent documents, missing fields, or conflicting records.
• Familiarity with end-to-end application stacks; Next.js and Convex are used, though equivalent experience is relevant.
• Care for versioning and reviewing prompts or other inputs to reasoning systems.
• English fluency for engineering collaboration and written review.

Responsibilities

• Develop the agent runtime that brings together tools, memory, and retrieval across differing validation needs.
• Build extraction pipelines that attach confidence information and source references to values, including incomplete inputs.
• Maintain evaluations using reference sets, regression checks, and drift monitoring.
• Implement validators from specifications and record validation results in the audit trail.
• Design provider interfaces that support mock providers during development and production providers without a rewrite.
• Provide observability to let teams understand agent behavior in production.

Job description

Role overview

Build and maintain the runtime that makes AI agent outputs traceable and reviewable across different engagements. The work combines extraction, validation, evaluation, provider integration, and observability so reviewers can inspect both an output and its supporting source.

Responsibilities

• Develop the agent runtime that brings together tools, memory, and retrieval across differing validation needs.
• Build extraction pipelines that attach confidence information and source references to values, including when inputs are incomplete, scanned, inconsistent, or contradictory.
• Maintain evaluations using agreed reference sets, regression checks, and drift monitoring to catch releases that should not ship.
• Implement validators from specifications, making failures visible and recording validation results in the audit trail.
• Design provider interfaces that support mock providers during development and production providers without a rewrite.
• Provide observability that lets teams understand agent behavior in production.

Requirements

• Experience shipping AI or agent systems into production, with strong typed software engineering practices.
• Experience building evaluation or monitoring systems that detect meaningful regressions.
• Ability to handle imperfect real-world inputs such as scans, inconsistent documents, missing fields, or conflicting records.
• Familiarity with end-to-end application stacks; Next.js and Convex are used, though equivalent experience is relevant.
• Care for versioning and reviewing prompts or other inputs to reasoning systems.
• English fluency for engineering collaboration and written review.

Nice to have

• Experience with regulated or safety-relevant systems; this is not required.

Benefits and work setup

• Remote work with at least four hours of overlap with CET on working days; occasional travel for engagement kickoffs.
• Contract or full-time arrangements are available. Contract engagements have a defined scope and may convert to full-time.
• Compensation is discussed during the written exchange and varies with engagement type and location.