JetBridge AI

• Act as the primary technical point of contact for our healthcare "vibe coders," diagnosing and resolving complex platform and code-level issues. • Design, build, and maintain full-stack features, internal tooling, and diagnostics that prevent developer friction before it happens. • Write optimized SQL queries, design robust schemas, and develop secure, type-safe REST APIs to expand platform capabilities. • Take features from concept to production end-to-end, while working closely with the core engineering team to loop developer feedback back into the product.

• Build predictive models (forecasting, time series, trend analysis) on real-world program and financial data. • Design anomaly / outlier detection to surface risks, inefficiencies, and non-obvious patterns. • Own feature engineering, model evaluation, and interpretability (feature importance, SHAP-style analysis). • Work end-to-end from exploration → modeling → business-facing insights. • Partner with product and analytics teams to turn models into decisions.

• Clean up, refactor, and modularize a rapid-prototype React/Next.js frontend. • Design and implement a robust, production-ready backend architecture from scratch. • Move direct LLM API calls into a structured orchestration layer. • Build and optimize advanced prompt engineering workflows and image generation pipelines (specifically leveraging OpenAI's image generation models/DALL-E). • Set up data ingestion workflows to parse clinical study protocols. • Prepare and structure internal ad-performance training data for potential LLM fine-tuning. • Own the deployment, hosting, and monitoring strategy to transition the app from a fragile prototype to a stable, scalable MVP. • Ensure best practices for data handling (Note: the app processes study protocols and marketing data, not patient data/PHI, so full HIPAA/SOC 2 compliance is not required for this phase).

• Perform manual and exploratory testing on platform APIs, integrations, and interfaces. • Write clear, comprehensive test cases and detailed bug reports. • Partner with engineers to understand technical requirements and protect data integrity.

• Design, build, and maintain data pipelines to analyze complex behavioral health datasets. • Implement and fine-tune AI/ML models to identify clinical trends and predictive patterns. • Partner closely with the clinical team to explore clinical hypotheses, running the data queries and statistical analyses needed to prove or disprove them. • Act as the technical voice on scientific papers, abstracts, and whitepapers. You will translate data methodologies, model architectures, and statistical findings into clear, publication-ready text. • Turn raw data into compelling visualizations and narratives that can be easily understood by both medical professionals and the broader public.

• Build end-to-end features using TypeScript across the entire stack (Next.js/React and Node.js) • Design and optimize SQL schemas to handle complex, highly structured medical data • Create reusable components and APIs for third-party developers • Streamline CI/CD or integrate AI workflows to enhance platform capabilities • Ensure platform performance and reliability as data volume grows

• Build and maintain automated test suites using Python and PyTest • Own integration, system, and end-to-end (E2E) testing for backend services • Write and maintain REST API tests • Test services across emulated, dev, staging, and production-like environments • Validate data integrity using PostgreSQL / SQL • Work closely with software engineers in Agile/Scrum teams • Help identify and debug issues in distributed backend systems

• Build backend services with Node.js / TypeScript on AWS • Design event-driven systems using queues and async workflows • Develop React / Next.js frontend features • Build and consume APIs (API Gateway–style architectures) • Work with SQL-based databases for transactional workloads • Contribute to serverless infrastructure and cloud architecture

• Design and implement backend architecture that will shape the platform for years • Build GraphQL APIs for querying and analyzing genetic construct data • Develop services using Python, SQLAlchemy, and modern backend frameworks • Architect complex data models representing biological systems • Collaborate directly with scientists to understand workflows and translate them into software tools • Design systems that scale as usage and data volume grow significantly • Participate in on-call rotation and support production systems

• Partner with sales and GTM teams during enterprise technical discussions • Run live demos and build custom proof-of-concepts • Architect agent-user interaction patterns for real production systems • Hold weekly working sessions debugging customer code • Provide production-readiness guidance and design reviews • Capture customer feedback and advocate internally with engineering • Create technical walkthroughs and demo assets that convert