AI Application Engineer

ABOUT CT MEDTECH
CT MedTech builds healthcare AI grounded in real care. Our products span medical imaging, clinical decision support, laboratory and preventive-health analysis, telemedicine, and electronic medical records software used by doctors and patients in real clinics every day.
THE ROLE
We are hiring an experienced AI Application Engineer to design and lead the delivery of reliable, production-grade AI features inside our healthcare software.
You will build the application layer around large language and multimodal models: retrieval over medical knowledge, structured extraction from clinical documents and forms, image-understanding workflows, and the evaluation and safety controls that make AI output trustworthy enough for a clinical setting.
This is a senior engineering role. You will set the technical direction for our AI applications, own them from architecture through deployment, guide other engineers, and work closely with clinicians - measuring success by whether the system is accurate, safe, and useful in daily practice.
WHAT YOU WILL DO
Own the architecture and technical roadmap for our AI applications, and guide other engineers through design reviews, code reviews, and mentoring.
Design, build, and ship LLM-powered applications and agentic workflows - prompting, tool calling, structured outputs, and multi-step orchestration - integrated into our clinical platforms.
Build retrieval (RAG) pipelines over medical knowledge and clinic data: document ingestion, chunking, embeddings, vector search, and grounding answers in cited sources.
Develop multimodal workflows that analyze medical images and extract, translate, and digitize prescriptions, eyeglass orders, and other clinical forms.
Create evaluation frameworks - golden datasets, regression tests, and human-in-the-loop review - so every model or prompt change is measured before it reaches users.
Implement guardrails and human oversight: output validation, confidence handling, audit logging, and clear escalation to clinicians for anything that affects care - with patient data handled under strict privacy and access controls.
Integrate AI services with backend APIs and existing systems, and operate them in production with tracing, monitoring, and cost and latency control.
Use AI coding assistants in your own workflow, and share reusable prompts, patterns, and small internal tools with the team.
TECH STACK
Languages: Python, TypeScript, SQL
LLM & Vision: Gemini, Claude, OpenAI, open-source models, tool calling, structured outputs
Retrieval: embeddings, RAG, pgvector / vector DBs, hybrid search, re-ranking
Backend: FastAPI, [protected info], REST APIs, PostgreSQL
Quality & Ops: evals, LLM tracing, Docker, Git, CI
WHAT WE LOOK FOR
Must have
A Master's degree in Computer Science, Artificial Intelligence, Data Science, Biomedical Engineering, or a related field.
5+ years of professional software engineering experience, including substantial hands-on work shipping AI/ML or LLM applications to production.
Strong Python and software architecture skills: APIs, pipelines, and clean, maintainable systems.
Deep experience building on LLM APIs - prompting, tool calling, and structured outputs.
Practical experience with RAG: embeddings, vector search, and retrieval tuning.
A habit of measuring quality - you test AI output rather than trusting it, and you can explain how you would catch hallucinations.
Comfortable reading technical English and communicating clearly in a team.
Nice to have
Experience in healthcare, medical imaging, or other regulated domains.
Work with multimodal / vision models or document extraction (OCR, forms).
Agent frameworks such as LangChain or LangGraph, or a well-reasoned custom orchestration.
Evaluation and observability tooling, LLM-as-judge testing, and prompt regression tests.
Familiarity with open-source models, fine-tuning, or on-device deployment.
Deliberate use of AI coding assistants in your own workflow.
A portfolio or GitHub that shows how you build.
WHAT WE OFFER
Real ownership of AI features used in real clinics, with measurable impact on patient care.
A modern, AI-first engineering culture that rewards rigor, initiative, and craft.
A small, senior team where you shape technical decisions and your work is visible.
Competitive compensation, room to grow, and continuous learning.