AI Engineer for Large Language Model (LLM) Products - Remote

About dexter health

dexter health develops AI-driven software solutions for healthcare teams, aiming to reduce administrative burdens on caregivers so they can dedicate more time to patient care.

Role Overview

We are seeking a highly proactive AI Engineer to accelerate the creation of new AI functionalities and enhance the performance, stability, and efficiency of current AI workflows. This hands-on role focuses on converting vague product concepts into production-grade AI capabilities, primarily centered on shipping AI features with involvement in AI infrastructure and systems as required.

Key Responsibilities

• Develop and deploy AI-powered product features from concept through production.
• Enhance existing AI workflows to improve quality, reliability, speed, and user benefit.
• Architect LLM-based processes including output structuring, validation, and fallback mechanisms.
• Create evaluation cycles, testing routines, and quality assurance for AI outputs.
• Integrate AI functionalities into current product backends and systems.
• Work flexibly with various commercial and open-source LLMs without vendor lock-in.
• Support self-hosted model workflows enhancing quality, speed, cost, or control.
• Diagnose AI feature issues spanning inputs, outputs, data, backend logic, and user experience.
• Utilize AI development tools like Claude Code, Codex, Cursor, Copilot daily.
• Deliver solutions rapidly while maintaining production-level quality.

Candidate Requirements

• Proficient software developer with strong skills in Python or equivalent backend language.
• Practical experience creating AI-powered features or LLM workflows.
• Ability to swiftly translate loosely defined product ideas into functional software.
• Solid understanding of designing, testing, validating, and improving AI-generated results.
• Experience integrating AI processes within production-grade systems.
• Keen debugging skills encompassing application logic, data handling, model outputs, and user interface behavior.
• Expertise in evaluation, testing, validation, or quality control of AI outputs.
• Regular user of AI development platforms such as Claude Code, Codex, Cursor, Copilot, or similar.
• High intellectual capacity, rapid learning, proactive attitude, and strong ownership.
• Comfortable working under ambiguous conditions with quick decision-making in a high-trust startup culture.
• Fluent in written and spoken English.

Preferred Qualifications

• Background in frontend or full-stack development.
• Familiarity with self-hosted LLMs, serving models, and optimizing inference.
• Experience deploying and maintaining open-source LLMs.
• Proven ability to enhance AI system latency, cost-effectiveness, quality, or reliability.
• Exposure to healthcare software, data, or regulated environments.
• Experience with structured data extraction, documentation automation, voice-driven workflows, or automation of workflows.
• Knowledge of German language.
• Understanding of nursing home or elderly care operations.

What This Role Is Not

• This position is not focused on machine learning research.
• Not suitable for prompt engineers lacking solid coding capabilities.
• Not appropriate if you require detailed specs prior to progressing.
• Unsuitable for individuals preferring slow, highly regulated corporate settings.
• Not a managerial role; requires hands-on development.
• Requires daily usage of AI development tools, not occasional use.
• Not for those prioritizing flawless processes over rapid, reliable execution.

Benefits

• Fully remote work setup.
• Competitive pay that reflects skills, experience, and location.
• Ownership responsibilities over critical backend systems.
• Opportunity to develop software directly used in healthcare workflows.
• Modern, AI-focused development environment.
• Growth potential alongside the company.

Mission

Healthcare professionals often face excessive documentation and administrative duties. Our technology alleviates these burdens by leveraging AI as a fundamental product component. Creating impactful AI features requires strong engineering, rapid iteration, thorough evaluation, and dedicated focus on user outcomes. If you want to be part of a fast-paced team building AI features that improve real-world workflows, engage daily with AI tools, and take ownership, we encourage you to join us.