Start Date
Immediate
Expiry Date
29 Dec, 26
Salary
2400000.0
Posted On
30 Sep, 26
Experience
1 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Industry
Information Technology & Services
👋 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 AI Engineer, you will:
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
Nice-to-have
This role is probably not for you if
Benefits
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.
AI and Generative AI Engineer with over two years of experience designing, building, and deploying production-grade Large Language Model systems, AI agents, and Retrieval-Augmented Generation pipelines. Skilled in LangChain, LangGraph, Hugging Face, FastAPI, and multi-agent architectures, having delivered 4+ production applications while reducing AI workflow latency by approximately 30 percent and improving accuracy by approximately 35 percent. Brings strong enterprise engineering discipline from Accenture, having supported 25 or more projects with up to 80 percent process automation, combined with a solid foundation in deep learning, vector search, and cloud-based deployment. Holds a Master of Science in Applied Artificial Intelligence from Cranfield University, United Kingdom, and is available to join immediately.