Full-Stack Engineer – AI Clinical Research Platform

Tilda Research

. Build and ship production features across the frontend and backend, with approximately a 50/50 split .

Posted 11/9/2026full-timeRemote • ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong full-stack development capabilities with expertise in React, Python, and Node.js/TypeScript, alongside experience in integrating AI technologies into software solutions. Proven ability to manage the software development lifecycle, from design to deployment, while collaborating with cross-functional teams in a clinical or regulated environment.

Highest-signal resume keywords

Full-Stack DevelopmentReact FrameworkPython DevelopmentAPI Design and DevelopmentAI Integration

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Applicant Tracking System Keywords

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Hard Skills

Full-Stack DevelopmentReactPythonNode.jsTypeScriptREST APIsSQLSaaS ApplicationsCloud EnvironmentsAI-Powered Features

Soft Skills

Problem-SolvingCommunication

Tools & Technologies

AWSGCPAzureDocument Processing SystemsEvent-Driven Architectures

Industry Keywords

HealthcareClinical ResearchLife SciencesRegulated IndustryEnterprise Applications

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaScriptNode.jsPythonReactSQLTypeScript

About the role

Key responsibilities & impact

Build and ship production features across the frontend and backend, with approximately a 50/50 split
Develop modern, intuitive web experiences using React or similar frontend technologies
Design and build backend services, APIs, data models, integrations, and application logic using Python, Node.js/TypeScript, or similar technologies
Own features end-to-end, from technical design and development through testing, deployment, and production support
Integrate LLMs and AI capabilities into product workflows, including document processing, classification, data extraction, search, summarization, and workflow automation
Build human-in-the-loop AI experiences that allow users to review, approve, correct, and interact with AI-generated work
Partner with Product, Design, and clinical domain experts to turn complex clinical workflows into simple, scalable software
Participate in architecture discussions, code reviews, testing, debugging, and continuous improvement of engineering practices

Requirements

What you’ll need

4+ years of professional software engineering experience
Strong hands-on full-stack development experience with approximately a 50% frontend / 50% backend split
Strong experience with a modern frontend framework such as React
Backend development experience using Python, Node.js/TypeScript, or similar technologies
Experience designing and consuming REST APIs
Strong understanding of relational databases and SQL
Experience building and supporting production SaaS applications
Experience with cloud environments such as AWS, GCP, or Azure
Strong understanding of modern software-development practices, testing, debugging, and code quality
Ability to independently own features across the software-development lifecycle
Strong problem-solving and communication skills
Ability to communicate in English with Product Teams, Engineering teams and Customers
Experience with one or more of: LLM APIs such as OpenAI, Anthropic, or Gemini; AI agents or agentic workflows; prompt engineering and structured outputs; AI-powered document processing or data extraction; retrieval, search, and summarization; human-in-the-loop AI workflows; AI evaluation, monitoring, and observability
Experience shipping AI-powered features into production is strongly preferred
Experience in a startup or high-growth SaaS environment is preferred
Experience with healthcare, clinical research, life sciences, or another regulated industry is preferred
Experience building workflow-heavy enterprise applications is preferred
Experience with third-party APIs and system integrations is preferred
Experience with document-management or document-processing systems is preferred
Familiarity with event-driven or asynchronous architectures is preferred
Experience with production monitoring and observability is preferred