Description review
Applied AI Developer - Remote
dexter health · Germany · back to the listing
HR standards
52/100
needs work
Title ↔ description
81/100
solid
Reads as
Machine Learning Engineer
82% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
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- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- 42 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
👋 Welcome to dexter health!
At dexter health, we build AI-powered software for care teams. Our mission is to reduce administrative workload in healthcare so caregivers can spend more time with patients.
We are looking for a high-agency AI Engineer to help us build new AI features faster and improve the quality, reliability, and speed of existing AI workflows.
This is a hands-on engineering role. Not research. Not prompt-only. You will turn ambiguous product ideas into working, production-ready AI features.
The role is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
You will work closely with product and engineering, but we expect you to take real ownership. You should be comfortable moving fast, making technical decisions under ambiguity, and using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar every day.
Tasks
As our Applied AI Engineer, you will:
• Build new AI-powered product features from idea to production
• Improve existing AI workflows for quality, reliability, latency, and user value
• Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior
• Build evaluation loops, tests, and quality checks for AI-generated outputs
• Integrate AI capabilities into existing product and backend systems
• Work with commercial and open-source LLMs without being tied to one specific provider
• Support self-hosted model workflows where they make sense for quality, speed, cost, or control
• Debug AI feature failures across inputs, outputs, data, backend logic, and user flows
• Use AI development tools as a core part of your daily workflow
• Ship quickly while keeping production quality hi
Requirements
We care less about formal seniority and more about speed, intelligence, ownership, and product impact. We like people who operate with founder-like urgency: they figure things out, make progress under ambiguity, and care about outcomes more than titles.
Must-have
• Strong software engineering skills, especially in Python or a comparable backend language
• Experience building AI-powered product features or LLM-based workflows
• Ability to turn ambiguous product ideas into working software quickly
• Strong understanding of how to design, test, validate, and improve AI outputs
• Experience integrating AI workflows into production systems
• Strong debugging instincts across application logic, data, model outputs, and user-facing behavior
• Experience with evaluation, testing, validation, or quality checks for AI-generated outputs
• Serious experience using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar as part of your daily workflow
• High intelligence, fast learning speed, bias to action, and ownership mindset
• Comfortable with ambiguity, fast decisions, and a high-trust startup environment
• Clear written and spoken English
Nice-to-have
• Experience with frontend or fullstack product development
• Experience with self-hosted LLMs, model serving, inference optimization, or similar systems
• Experience with open-source LLMs and related deployment workflows
• Experience improving latency, cost, quality, or reliability of AI systems
• Experience with healthcare software, healthcare data, or regulated environments
• Experience working with structured data extraction, documentation automation, voice workflows, or workflow automation
• German language skills
• Knowledge of nursing homes or elderly care workflows
This role is probably not for you if
• You are mainly looking for an ML research role
• You are a prompt engineer without strong coding skills
• You need detailed specifications before making progress
• You prefer slow, highly structured corporate environments
• You are mainly looking for management, not hands-on building
• You want to use AI tools only occasionally instead of as part of your daily workflow
• You optimize for perfect process over fast, reliable execution
Benefits
• Remote work
• Fair compensation based on skills, experience, and location
• Ownership of important backend systems
• Work on software used in real healthcare workflows
• Modern AI-native development workflow
• Room to grow with the company
Why?
Caregivers spend too much time on documentation, coordination, and administrative work. We build technology that reduces this burden.
AI is core to our product. But useful AI features do not come from demos alone. They need strong engineering, fast iteration, evaluation, production thinking, and deep ownership of the user outcome.
If you want to build AI product features that ship, improve real workflows, use AI tools every day, and take ownership in a fast-moving team, we would like to hear from you.
Originally posted on Himalayas
At dexter health, we build AI-powered software for care teams. Our mission is to reduce administrative workload in healthcare so caregivers can spend more time with patients.
We are looking for a high-agency AI Engineer to help us build new AI features faster and improve the quality, reliability, and speed of existing AI workflows.
This is a hands-on engineering role. Not research. Not prompt-only. You will turn ambiguous product ideas into working, production-ready AI features.
The role is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
You will work closely with product and engineering, but we expect you to take real ownership. You should be comfortable moving fast, making technical decisions under ambiguity, and using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar every day.
Tasks
As our Applied AI Engineer, you will:
• Build new AI-powered product features from idea to production
• Improve existing AI workflows for quality, reliability, latency, and user value
• Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior
• Build evaluation loops, tests, and quality checks for AI-generated outputs
• Integrate AI capabilities into existing product and backend systems
• Work with commercial and open-source LLMs without being tied to one specific provider
• Support self-hosted model workflows where they make sense for quality, speed, cost, or control
• Debug AI feature failures across inputs, outputs, data, backend logic, and user flows
• Use AI development tools as a core part of your daily workflow
• Ship quickly while keeping production quality hi
Requirements
We care less about formal seniority and more about speed, intelligence, ownership, and product impact. We like people who operate with founder-like urgency: they figure things out, make progress under ambiguity, and care about outcomes more than titles.
Must-have
• Strong software engineering skills, especially in Python or a comparable backend language
• Experience building AI-powered product features or LLM-based workflows
• Ability to turn ambiguous product ideas into working software quickly
• Strong understanding of how to design, test, validate, and improve AI outputs
• Experience integrating AI workflows into production systems
• Strong debugging instincts across application logic, data, model outputs, and user-facing behavior
• Experience with evaluation, testing, validation, or quality checks for AI-generated outputs
• Serious experience using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar as part of your daily workflow
• High intelligence, fast learning speed, bias to action, and ownership mindset
• Comfortable with ambiguity, fast decisions, and a high-trust startup environment
• Clear written and spoken English
Nice-to-have
• Experience with frontend or fullstack product development
• Experience with self-hosted LLMs, model serving, inference optimization, or similar systems
• Experience with open-source LLMs and related deployment workflows
• Experience improving latency, cost, quality, or reliability of AI systems
• Experience with healthcare software, healthcare data, or regulated environments
• Experience working with structured data extraction, documentation automation, voice workflows, or workflow automation
• German language skills
• Knowledge of nursing homes or elderly care workflows
This role is probably not for you if
• You are mainly looking for an ML research role
• You are a prompt engineer without strong coding skills
• You need detailed specifications before making progress
• You prefer slow, highly structured corporate environments
• You are mainly looking for management, not hands-on building
• You want to use AI tools only occasionally instead of as part of your daily workflow
• You optimize for perfect process over fast, reliable execution
Benefits
• Remote work
• Fair compensation based on skills, experience, and location
• Ownership of important backend systems
• Work on software used in real healthcare workflows
• Modern AI-native development workflow
• Room to grow with the company
Why?
Caregivers spend too much time on documentation, coordination, and administrative work. We build technology that reduces this burden.
AI is core to our product. But useful AI features do not come from demos alone. They need strong engineering, fast iteration, evaluation, production thinking, and deep ownership of the user outcome.
If you want to build AI product features that ship, improve real workflows, use AI tools every day, and take ownership in a fast-moving team, we would like to hear from you.
Originally posted on Himalayas