Senior/Staff Software Engineer (Full Stack)

Senior/Staff Software Engineer (Full Stack)

About the Organization

We are an AI-powered technology firm dedicated to transforming how the pharmaceutical, biotechnology, and life sciences investment communities manage portfolios, conduct due diligence, and simulate value versus risk. Our platform accelerates the path for breakthrough therapies by:

• Empowering Life Sciences Leaders: Accelerating drug pipelines and maximizing ROI to achieve clinical success and greater patient impact.
• Strategic Asset Positioning: Enabling precise valuation of assets during critical portfolio planning and deal-making phases.
• Optimizing Capital Allocation: Providing investors with data-driven insights to refine drug asset transactions.

Supported by premier venture capital firms, we are on a mission to unlock the full potential of pharmaceutical R&D by providing decision-makers with real-time, actionable insights.

The Opportunity

We are seeking an exceptional Senior/Staff Software Engineer to build and lead our core platform during a pivotal growth stage. This is a rare opportunity to serve as the Technical Lead for a high-impact platform, ensuring our global pharmaceutical partners achieve transformative outcomes. Our solution is experiencing exceptional demand and is backed by top-tier life science investors who recognize the profound impact AI can have on the industry.

Responsibilities

• End-to-End Platform Ownership: Design, build, and scale the web architecture that allows deal teams to explore, upload, and analyze drug assets from discovery through due diligence.
• Front-End Architecture & UX: Develop intuitive, data-rich interfaces using modern frameworks (React/Next.js preferred) that allow users to manage pipelines and interpret complex, AI-driven insights.
• Workflow & Orchestration: Implement robust backend services and job orchestration layers (e.g., FastAPI, Node.js) to coordinate document ingestion, model execution, and results delivery.
• Data Visualization: Create dynamic, interactive components to visualize scientific assessments, risk analyses, and deal insights generated by machine learning pipelines.
• API & Integration Engineering: Design and maintain clean, scalable APIs between the core orchestration layer and the platform, collaborating with ML engineers to translate model outputs into user-ready insights.
• Reliability & Scalability: Deploy and monitor services on cloud infrastructure (AWS preferred), ensuring high availability, low latency, and secure handling of sensitive data.
• Collaboration & Product Thinking: Work cross-functionally with ML engineers, product leads, and domain experts to translate scientific logic into actionable workflows.
• Continuous Improvement: Champion engineering best practices—including automated testing, CI/CD, and modular architecture—while staying current on AI-driven development.

Qualifications

Core Requirements

• Education: Bachelors, Masters, or Ph.D. in Computer Science, Software Engineering, or a related technical field.
• Full-Stack Engineering: Proven experience building modern web applications end-to-end, from performant front-ends (React, Next.js) to scalable back-ends (FastAPI, Node.js).
• Product & Platform Development: Hands-on experience implementing complex, data-driven applications that integrate with APIs, asynchronous systems, or ML backends.
• Frontend Architecture: Strong command of component-based design, state management, and visualization frameworks (e.g., React Query, Redux, D3, Plotly).
• Backend & API Engineering: Expertise in developing RESTful or GraphQL APIs, managing authentication/authorization, and event-driven workflows.
• Database & Data Flow: Proficiency with both relational and NoSQL databases (e.g., Postgres, MongoDB, DynamoDB) and designing efficient data access layers.
• Cloud Infrastructure & DevOps: Experience deploying full-stack applications (AWS, GCP, or Azure) using modern DevOps practices (Docker, Kubernetes, Terraform, CI/CD).
• Security & Compliance: Familiarity with best practices for secure data handling and user authentication within enterprise or healthcare environments.
• Collaborative Mindset: Ability to work closely with specialized engineers and domain experts to deliver high-impact user workflows.

Professional Competencies

• Strong analytical mindset and problem-solving skills.
• A passion for continuous learning and rapid, user-centric iteration.
• An autonomous, self-starter attitude with a high degree of ownership.
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Bonus Points

• Experience in the healthcare, life sciences, or biopharma sectors is preferred but not required. We value a strong curiosity about the drug development process and the mechanics of industry deal-making.