Company Description

For over 20 years, Cancer Monthly has helped cancer patients and their families navigate one of

the hardest diagnoses in medicine. We've built a deep library of patient-focused cancer

content, held thousands of patient conversations, and maintain working relationships with

treating physicians, RN navigators, and various resources patients often need. That

accumulated knowledge is the foundation for what we're building next.

Role Description:

You will design and build our AI patient navigator: a conversational system that answers

patients' questions about their cancer using our content library, our internal database, and

vetted medical literature. It should guide each patient to the next step that actually helps them.

This is not a chatbot project. A chatbot answers questions; this system has goals. It needs to

understand where a patient is in their journey, earn their trust one solved problem at a time,

and know when (and when not) to introduce our resources. You'll own that experience end to

end: the conversation design, the retrieval architecture behind it, the guardrails, and the

product decisions in between.

You'll work directly with the founder. You'll ship early prototypes fast, put them in front of real

patient scenarios, and iterate.

What You'll Do

• Architect and build the navigator: LLM application layer, RAG pipeline over our content

and curated medical sources, and grounding/citation so every clinical answer traces to a

credible source.

• Design the conversation itself such as the first five minutes with a newly diagnosed

patient.

• Build guardrails that keep the system inside its lane: no diagnosis, no treatment advice,

clear escalation paths to human navigators.

• Implement transparency by design. Patients should understand what the system is,

what it draws from, and how we're connected to the resources it mentions.

• Work with our clinical reviewers to validate answer quality and keep the knowledge

base current

• Ship a working prototype in your first 60-90 days, then iterate toward production

Required

• 4+ years of software engineering experience, including production web applications
• Hands-on experience shipping LLM applications to real users, not demos or side projects
• Strong RAG experience: retrieval design, embedding/chunking strategy, retrieval

evaluation, and grounding responses in source documents

• Fluency with Anthropic and/or OpenAI APIs and modern LLM tooling
• Demonstrated product judgment, you've made calls about what to build and why, not

just how

• Experience designing multi-turn conversational or agentic systems (systems with goals

and state, not single-shot Q&A)

• Comfort working directly with a non-technical founder; you communicate clearly and

often

• Sound judgment about operating in a regulated, high-stakes domain, you build

conservatively where the cost of a wrong answer is high

Strongly Preferred

• Experience in healthcare, health tech, or another regulated industry (HIPAA, FDA SaMD

boundaries, or equivalent)

• Conversation design or UX design experience
• Prior startup founder or founding-engineer experience
• Oncology or patient-navigation domain exposure

Note: we don't require deep oncology knowledge — we supply that. We do require the

judgment to know what you don't know and to defer to clinical review.

What Makes This Role Different

Most AI engineering roles optimize a pipeline. This one optimizes trust. The people using this

system have just received devastating news. Every design decision, tone, pacing, when to offer

a resource, when to hand off to a human, affects whether they get help or give up. If that

responsibility sounds motivating rather than intimidating, we should talk.

Compensation

• This is a 1099 independent contractor engagement
• $110–$160 per hour depending on experience, invoiced [weekly / semi-monthly]
• No benefits, equity, or withholding; contractors are responsible for their own taxes,

insurance, and equipment

To Apply

Send a resume plus a link to an AI product you built that we can try ourselves. Include a short

note on one product decision you made while building it and why. If your best work is

proprietary or no longer live, send a brief video walkthrough or case study instead — and be

ready to demo it in your first interview. Applications without a work sample won't be

considered.

Qualifications

• Strong analytical skills to interpret user data, patient journeys, and product performance metrics.
• Hands-on experience in product engineering and product design for AI or software solutions.
• Excellent communication skills for collaborating with cross-functional teams and explaining complex concepts clearly.
• Background in research and development (R&D), including prototyping, testing, and iterative improvement of digital products.
• Understanding of healthcare workflows, patient experience, or digital health tools is highly beneficial.
• Ability to work independently in a remote environment, manage multiple priorities, and meet deadlines.
• Proficiency with relevant tools or languages for AI product development (e.g., Python, APIs, data analysis platforms) is an advantage.
• Bachelor’s degree in engineering, computer science, healthcare informatics, or a related field, or equivalent practical experience.