C the Signs

C the Signs is a cancer prediction system that can identify patients at risk of cancer at the earliest and most curable stage of the disease. In under 30 seconds, C the Signs can rapidly identify…

cthesigns.com

C the Signs

C the Signs is a cancer prediction system that can identify patients at risk of cancer at the earliest and most curable stage of the disease. In under 30 seconds, C the Signs can rapidly identify…

cthesigns.com

HQGB

Team Size39

Open JobsUnknown

Total Funding-

Latest FundraiseUnknown

TL;DR

What they do: AI clinical decision support that identifies patients at risk of cancer earlier in primary care

Regulatory status: MHRA Class I medical device

Primary integrations: EMIS and SystmOne

Reported scale: >400,000 risk assessments; 50,000–70,000 cancers detected (company-reported)

Notable investors: MMC Ventures; Khosla Ventures; CancerX (listed among investors)

Company Overview

Problem Domain

Early cancer detection in primary care

Industry

Hospitals and Health Care

Funding Track Record

Series A- 2022-02-04

Venture- 2025-01-30

Crunchbase lists a total of six funding rounds and seven investors (additional rounds not individually detailed in evidence)

Investor Signal

“MMC Ventures; Khosla Ventures; CancerX Startup Accelerator listed among investors”

Founders

What we do

Join the Team

Senior AI Developer (Agentic Healthcare Application)

On-SiteRhode Island, US

On-Site • Rhode Island, US

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Role Overview

We are looking for a forward-thinking Senior AI Developer to architect and build the next generation of autonomous AI applications. You will move beyond standard prompt engineering to design Agentic Workflows—systems where LLMs function as reasoning engines that can plan multi-step tasks, utilize external tools (APIs, databases), and collaborate with other specialized agents to achieve high-level goals.

You will contribute to the technical implementation of "Agency" in our software, transforming passive AI responses into active, goal-oriented behaviors.

Experience working with the GCP Vertex AI ecosystem is essential. In this role, you will design agents capable of complex reasoning and tool usage, leveraging Google’s managed infrastructure (Vertex AI Vector Search, Cloud Run, and BigQuery) to ensure reliability, security, and performance.

Requirements Key Responsibilities

Required Technical Skills

Core AI: Deep proficiency with LangChain or LangGraph, and specific experience with the Vertex AI SDK and ADK (Agent Development Kit)
Conversational workflow: Google Dialogflow CX
LLMs: Expertise in prompting and configuring LLMs, specifically utilizing Function Calling and Context Caching.
Experience with integrating LLMs into platform and application workflow, experience with MCP protocols
RAG/Embeddings: expert level experience in design and implementation of RAG based system using embeddings and vector databases
Data Engineering: Strong SQL skills for BigQuery; experience with Vector Databases (Pinecone, Milvus, or Vertex Vector Search)

Qualifications

Experience:
5+ years of software development experience.
2+ years of hands-on experience building and deploying enterprise-grade agentic applications (e.g., using LangGraph, LangChain Agents).
Familiarity with scalable, enterprise-level distributed systems
Experience with advanced data structures, algorithms, and complexity analysis
Demonstrated history of product value delivery

Education:

Bachelor's degree in Computer Science, Computer Engineering, or a closely related quantitative field is required.
Master's degree in Artificial Intelligence, Machine Learning, or a relevant field is strongly preferred.

Work Authorization:

Must be a US Citizen, Green Card holder, or currently in the US having a valid H1B visa

Benefits Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact.

Benefits:

Competitive salary and benefits package.
Flexible working arrangements (remote or hybrid options available).
The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

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Architecting and Implementing Agentic Workflows

Design Autonomous Loops: Build stateful control loops (Perception -> Reasoning -> Action) where agents can interpret clinical data, plan necessary checks, and generate risk assessments.

Conversational Agentic workflow: Chatbot style user experience powered by LLM

GCP Integration: Leverage Vertex AI for model serving and LLM models for reasoning, optimizing for long-context windows to process complex medical history.

RAG & Grounding: Implement "Enterprise Grounding" using Vertex AI Vector Search to ensure all agent outputs are strictly cited against official medical literature (e.g., medical research and guidelines).

Data & Tool Integration

Structured Data Access: Build robust Python tools (Function Calling) that allow agents to securely query BigQuery or other datastores for patient demographics and symptoms.

Security & Compliance: Ensure all AI operations comply with HIPAA/GDPR standards, implementing strict PII masking and data governance within the Google Cloud environment.

System Reliability: Deploy agents on Vertex AI, Cloud Run, or GKE, ensuring low-latency inference and high availability for clinical users.

Agent monitoring: implement effective product environment AI Agent execution monitoring and alert system to ensure SLA, safety and security compliance

Leadership & Strategy

Mentorship: Guide a team of engineers in MLOps best practices (CI/CD for models, evaluation pipelines).

Evaluation: Implement "LLM-as-a-Judge" frameworks to automatically test agent accuracy against "Golden Datasets" of clinical cases.

Backend Engineering: Mastery of Python (FastAPI) and containerization (Docker) for deploying microservices to Cloud Run or GKE.

Healthcare Domain: Familiarity with handling unstructured medical text or clinical guidelines is highly preferred.